August 1, 1956 REPORT f OF LANDS AND FORESTS Tee ene fo) OOLF OCeco NT EON TS Deer Inventory, Sioux Lookout District, 1955. - by J. A. Macfie Deer Range in Tweed District, 1955. = by Ps RS Thompson The Western Region Deer Check Station. - by R. Boultbee Structure of the Deer Herd in Western Region. - by R. Boultbee Recuperative Powers of Western Region Deer Herd. - by R. Boultbee Mortality in the Western Region Deer Herd. - by R. Boultbee Deer and Elk Inventories, North Bay District, 1955. = by Ge O¢ Bartlett: Deer Season in North Bay District, 1955. - by C. O. Bartlett Some Distortions in Deer Kill Curves from Ontario. - by H. G. Lumsden Deer Inventory, District of Sault Ste. Marie, 1955. - by M. W. Ts Smith Deer Survey, Sault Ste. Marie District, 1955. = by M. W. Ls Smith Elliott-Haynes Report. (THESE REPORTS ARE FOR INTRA-DEPARTMENTAL INFORMATION AND NOT FOR PUBLICATION) 1m 16 20 2 28 Al 56 61 66 aT ar f Gere, Otero s ‘ » : s¢ ta BS Ae bom! CEC L PER IB IS TG: (ox Boss sYapraoval a if : Me , ag eel aver © ie chew a 2eYMORT eA yh RS me y : ‘ ; f mb } nope ; ony We be ie CF & Y ae i noiteadge AON vresd ‘nolte yo «fh vd « iar, te y | i Saas Tolman ovsdaeW ak ben: x03 arta, ofee | yt * y aad ~ ebish ood sofpek asetesW to e-ren08. ey, MiInod ix « | he , lel esd colsed mrs 7B8W ‘gad 4% or ei y! - r e : : " ‘ . ‘oa . 5) ju i , co oY 2 * . 1 TIL LIE ‘ : VBE te ron Bo retaowal Sits 5 Oks qd « ‘OL ,cobrinkt yet Adwow Tei J » i 6 v< - : tyacn0 mol gevty). LO2% ten aL ee + Nn 3 s . vo - a 7 , jen *% ov [ 49 +a)" . 7H JIT upe ta ti re Po ei vd bated * 7 * ’ ry V2OL dobtsebis sits 2090 Ji #7) i on” ot off eit yo a ei 7 ee TATUM? ATID ANTT HOF “aia ans (WOT ADEE ROW. | 20% ath ee DEER INVENTORY, SIOUX LOOKOUT DISTRICT, 1955. by Je Ae Macfie This is the first deer inventory to be compiled for the Sioux Lookout district. It must be emphasized that in places almost pure guess-work had to be employed. Since trappers’? estimates of deer population have never been collected here, and we have little other information on density, the work is very weak at this point. Hunter kill is harder to assess for deer than for moose, due to the fact that a large proportion of the deer licenses are sold by outside agencies. While the Sioux Lookout moose, caribou and wolf inventor- ies include in their coverage all the area north of the C.N.R. in the Western Region, the deer inventory deals with the Sioux Lookout forest district only. The Kenora inventory will include that part of Patricia West administered by them, putting the inventories in line with the deer checking station work. Deer Population in December, 1954 In order to have a basis for a complete report for 1955, an inventory for the end of 1954 was compiled, and is included in this report. This was done by breaking down the band areas within the deer range to density zones varying from five deer per Square mile to one deer per 10 Square miles. A few more deer were added for areas of very low population. The resultant figure was 11,000 deer at the end of the 1954 hunting season. Wolf Kill During the Winter of 1954-55 Wolves were not particularly abundant, and snow conditions were in favor of the deer throughout the winter. The estimated kill of deer by wolves is 450. Other Losses During the Winter of 1954-55 Snow was not excessively deep, and at no time was there a crust. Added to that, spring came early, so deaths due to starvation must have been few. An arbitrary figure of 150 deer is set for this loss. The Indian kill during the winter is assumed to have accounted for an additional 100 deer. 1955 Fawn Cro Age composition data obtained this year at the Fort Frances checking station and in the district revealed that 20% of the deer killed by hunters were fawns. When this factor is applied to the assumed spring population of 10,300 deer, it is indicated that 2,575 fawns reached the hunting season. The surviving fawn crop then added 25% to the spring population. Weather was favorable during the fawning season, so the original fawn crop could not have been much greater than 3,500. P Ma . Te 1 ie TT) See a D Chel savas” 2 a of,’ if hy @ | a) ns ma) ae Bee . Mie ~ Be pens _ fe 1 99a H) {ih J. oe ° CARL ~TOLATETG syoudod meee ay er A Be 14 “ pis a, oe es 7" Liqnos od of yrotnevak wetb dettt eae Be BLaT , esualy { sand bestesraqme od veum cI ~cotEcBEp Juoxood 3 ‘ereqqait esata beyoiqms sd.od ban ATOW 829 UN) oti: bus .ore! betoeitos ad deven ever tolvalaqog, seob to asm uss W's 69% ‘t prow j JifrenreD no ror sei rro tat beet eldd cL | . 1e6b tol esesues ov tebiad ef Iliad segamm dnldge ‘ Le ; EY sovtel ea dede gon't gsit ot eu sofoness obLeguo * esocrevni Ifow bas vodiuso .osocam Jfetool sere ene otidw t To d2ven gorse of? 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Oe ect oto) 2 BerLy. oom need 1 Population in September, 1955 The spring population of 10,300 deer, plus the net increment of 2,575 fawns adds up to 12,875 deer reaching the hunting season. Allowing for a summer loss of 75 deer from road and railway kills, etc., we then had 12,800 deer at the beginning of the hunting season. Hunter Kill Non=resident: Non-resident hunters passing through the deer checking station killed 89 deer. In an incomplete canvass, tourist oute fitters reported 135 deer killed by non-residents from licensed camps. It is estimated that 200 deer in all were taken by non- residents. Residents: Department offices in the district sold 210 resident deer licenses. Licenses sold by outside agencies in the district, and hunters who purchased licenses in other districts, are estimated to have brought the total of resident hunters to 1,000. Available license book covers show that 60% of 119 hunters who hunted in 1954 got a deer that year. Success this year is thought tc have been comparable to last year, so the resident kill in 1955 may be placed at 600 deer. Population As Of November 25th., 1955. The September population of 12,800 deer, less the hunter kill of 800, leaves a population of 12,000, or 9% more than there were at the same time a year ago. ANNUAL INVENTORY OF DEER ON BAND AREAS District of Sioux Lookout Hstimated Population on Band Areas For the Fiscal Year 1954-55 Population on November 25th, 1955. Band Area Band Area (square miles) Deer Red Lake 5900 1,300 Lac Seul 6,400 6,900 Sioux Lookout P.W. 1,200 600 Sioux Lookout South 4,600 2,600 Savant-Armstrong-Auden 75900 250 Osnaburgh 6,100 is Pikangikum l,900 125 Rest outside main range 150 TOTALS 36,000 12,000 sod odt te teeb 008,S!. had acdd ow aoe es yew! diy eeol ,te0b 005,Sf to nofseluqog iédnodueell t » 489900 » CY to near ponte 6 20% iene Re s1OBBOB aaty { «SELBY is7oonrt ms if eis ol : etre rmnon vo bhelitet as0b 2€ VG WwW tis ni teh 0 aA y Fa tz . bfoe coittelbS ed? ar esokris Newsieqed ” ; I fonscas obilatve yd Bbloe es ‘ane eb aE $2 ; stb sa9ddo of soensotl beesiotng enw Bae 93 evodnud tosbigsi to fezos sid tdavosd sven oo Ye dour f lo &Oc tad? wore exevoo wood saneonas f «sey eidg sesoowe wisey dadé reeb 6 tom Bees [{ta taebiesy sdt on ,.teey deal oF eidaeitsqmed Has -rooh OGd Ja OCC ,dieS secmovoll I mtg etom RE to ,000,S1 to solteinuged 8 sevastis Be Wey 6 emis omnes CAUSA CMAS WO Aiea FO HOTU 4 i a iy s 2 #) 7 2 } - - I | U racY Isoseatt ef? rz04 esoxA bass ao no a ee ‘OL ,dce@S tredmevell nox eer + wae can fi AA a = 1g OOS. f Ow) A ’ ev 000 ,d€ oe Se ANNUAL INVENTORY OF DEER ON BAND AREAS District of Sioux Lookout Estimated Population on Band Areas For the Fiscal Year 1954 Population of deer at the end of 195k. Band Area Area Deer Red Lake 1/2 % 1200 aq. miles 600 1/4 x 1200 300 1/10 x 2500 250 Lac Seul § x S00 4,000 te 2100 2500 1/10 x 3500 350 Sicux FP, W. a: x 200 1.00 a710 x 1000 100 Sioux South be x 200 S00 2 x 550 bp LOO 1/10 x 4000 1.00 Savant-Armstrong 200 Auden 50 Osnaburgh 75 Pikangikum £25 Rest 150 TOTALS 11,000 Iuodoo.T xtrate to. “~ ~ Seti wpeY If soe fF. on »22l to fas off va 109.26 sottel oti esttA 00d solim spp O05 x S\I quesqy - e4TuM *eTtIn eaenbg seg szeeq gz 01 dn = Ha “OTT erzenbs Jeg 100d $-¢ - a °6G6T *3OTAASTG qnoyooT xXnoTS 19eq SuTMoys ueTd .* : ° e “s can @ : ee ay ee ae 2 " . / . LOTULSTG LAOWOOT XNOIs 9 ee 0 Eee te Uy o9) 16 > ue ob ag 4 ay it. a ae DEER RANGE IN TWEED DISTRICT, 1955 by P. A. Thompson In this report the abundance of deer on the respective areas is based on the following: 1. Inspection of deer yards during the winter of 1954-55. (a) South Canonto Township, January 25th & 26th, 1955. Deer were found to be concentrated in an area of approximately 4 to 6 square miles. No live deer were seen. The remains of two dead deer were found. There was no evidence to determine cause of death. Signs of heavy browsing was quite evident on what may be considered to be poor deer range. Deer of this area probably had a tough time surviving the winter. (b) Effingham Township, February 9th & March 23rd, 1955. This wintering area covered approximately 8 square miles. Deer trails were easily travelled without the aid of snowshoes. Over most of the area deer were spreading out from the trails and browsing on cedar, red maple, mountain maple, striped maple, black ash, juneberry, dogwood, hemlock and in one instance, balsam. In all 28 deer were seen, 13 on February 9th and 15 on March 23rd. Deer of this area were browsing on good range and appeared to be in top physical condition. No drastic complications were anticipated. (c) Sheffield Township, February 9th, 1955. This area is situated south of #7 Highway, northeast of Erinsville, and covers an area of 54 square miles. An abundance of good browse was available. As no deer has wintered in this area for some years, no trouble was anticipated. (d) Lake Township, January 15th, 1955. This area consisted of approximately 2 square miles and was patrolled by air only. Deer seemed to be wintering favourably. (e) Limerick Township, January 15th, 1955. Deer were yarded in an area of approximately 5 square miles. No ground inspection made, but deer appeared to be in good condition. 2e Aging data from deer checking stations: Barring weather conditions it seems quite reasonable to believe that the increase or decrease of a deer population is governed by the increase or decrease of the fawn production. Data collected from deer checking stations in the Tweed District over the past four years show that the fawn crop has increased by 9.8%. iw: 4 roagmod? fay) pee i) avisssqeot elt no tesh to psornabnidsa ait J Toqe'r a + = seitwollot end ig or ie -Cé-ARPL to tetmtw sds ydlawh ebyay sesh to notdosqe tn Bets ne mF io tay Tenios act ov herrot stay “ian oft stew toeb evil of »aelim etaupe a of a \leg . >} eshte bivse o paw stedT .bavot eraw teab bask owe siiup esw suisawotd yvvseed to Bs ng te Mess seb to eeusn 3807 ,stoax % 36b TOO” ¢ + bs d of bersi oo ed yea Jtadw a eISSN IW fd aniivivawe omic fA: rod ‘ tan yidedong f (d , nae myn prey S vie edacifxoiggs beteves get a abreseiie etsT) fire ais tveddiw belfloverd vilese sevew elisad ges sat > ; e a . "oof oer shots AsgaM 8 Age sees setmnantibtoned La a sg ne en ep acetate see oe one Ae te oti tro satbaeste straw BOR: oid to deom xevd [gem oissavom ,ciqsm bet ,18bso m6 gatavorwd baw iE DAS »zyoOLinedn qVOOW gab ett ery if, eh d oBid e2- a tO yisuadel no FL ,.nees Siew teeb SS Efe at —_ sd {oO ifeword enew sere efdt te weed ebrfS do ) J f 25 i ‘ae aii ey “i %3 [s: cay I ia) it ia , od Od og betes . betagtobinge 18W ‘pnd oOc8l p30 visyydel ,citfeawoT blattien (o) oF. {jyvoe betautte af sere * iT ¢ to £9%8 18 etevoo bas gen 8 fdsiisva asw eeword boom 26) O9tsqiolios esw eldyots on ,eteey emoe t0l Be ROL sivas T of ofim emsupe S$ yviectsmixotaga ‘to bedakenos pervs ef a tivsdnctw od ¢ smsee tee .¥ino: tig ad whe ial : amt . . re " - a i fl re VETS OTS by : pire: wot A2 eae ra p TSvp2 ¢ Ylevgamrxo1dgs To gers ig of bebray. ise al ed « heTseqqs teeh god ,ebam aotsooqen’ mae | a tolisew gntvish senotvece sakise eessotoni sit cad3 ib o? eldsnos a 10. 988et0rs£ odd vd bene Vox et noLs acfdseds twe)8h iors? bose foo aia oh x Season Percentage of Fawns in Sample Taken 1952 25.6% 1953 29.6% 1954 31.5% 1955 34.4% When information collected on the deer checking stations during the 1955 season is worked out by townships, it is quite evident that the townships with good winter range were responsible for the increase in fawn production. For comparison two groups of townships were formed. (a) In the townships of Herschel, Monteagle, Carlow, Faraday, Dungannon and Mayo, considered to have good winter deer range, 39% of the sample at checking stations were fawns. (b) In the townships of Matawatchan, Denbigh, Miller, Brougham, North Canonto and Blythfield, where the winter range is poor, only 22% of the deer sampled at checking stations were fawns. 3. Information on deer abundance supplied by hunters. 4. Weathers Weather conditions during the winter of 1954-55 were undoubtedly severe enough to cause above average mortalities, especially in the 14 year age class, However, these mortalitites seem to be localized to areas where winter range conditions are poor. anoitacs antdoedo toob edé ao béXeLLo9 nob cmmpebith a stivp at +E ,aqideawos ‘yd. dite” bedow.ef: tee feat ef{dissoqeox etew sunset astniw boo, Adiw. pee ges eqyorg owt noeiiagi0o tod *oidowboty: mvst ak "Be. - oaino Sree wol1s5 ,eigaocnoil eLerisittel to ‘ai tsiermos. es ‘ai er “a ‘teh tedniw boon evad o7 bexsbiescod .oveas. bas: sons J -26WwSt otew enoitsde anidoods ta ofqnee edt 7 ,ISILiM .dgidaed ,sedotewstaM te a arom etkt nk td} t) ef osner iotniw eds eredw ,biottdtyif bas odnoned ds10f senwet crew exotiedte satdoods te be Lamar t99b ont to RS! t cc seretaud yd bet laque eonsbauds need ne som Stow CeestOLl to tedaiw edd gutted erigbethaoe edge - .celoiiscerom essis¥s evods eeasss od -dgvone seticitlssiow eaedd , 3 m NS Ae at is’ 2 ” fe Ye tS FE eS ef at ehfety 3é fiawodsis boas ateab wet ong ities . wolsed sidsi edd es Isteaus en tom ek JE Mota - * otn nuvlos s1txe MA .Mmiot oyscnsoteq HE ASE Bee tab f -STB9yY SSstds sat tot a 9o'rsag enetev apete f seel edd jabiem ot srecy settt {is ot aavan eae a 4) a 7 fi . 1) ae i ‘ert : . bes Ve Age Class 1953 1954, 1955 Three Years’ Average 2 21.4 1641 20.6 PG al le 29 att et Phe 220k 25 ae 26 re PS Jlez ane Gal 33 12.9 139 tes lhe7 he Dad 4.6 8.0 Ove 23 aut Seo 330 Bae 63 2el 367 iced 200 le 1.8 200 Awd Rok 83 Gee Ga 7 iyG 0.6 i 0.0 0.0 0.0 0.0 TOTALS 100.0% 100.0% 100.0% 100.0% The last column is the important feature of the table. It is a standard to which all other items may be compared to establish their importance. Three years are a small basis to use for a standard but a survey of the three consecutive game check stations operated to date is necessary to prove their importance. The three year averages coupled with judgement can already be a valuable means to help us envisage our deer herd as it actually is, and this is the first requirement of sound management. If we patiently accumulate nine or ten years’ data, the averages will be an unquestionable basis for judging the condition of the herd. There are already eleven fawn crops incorporated in the table but nine or ten years’? data will follow that number of fawn crops from start to finish. Nine or ten years’ data should also include a fair share of hard, ordinary, and good winters and should make the averages reasonably representative of normal conditions. The table of percentages can be used to judge the shape of the herd as found in the annual check, and also to follow the course of any one fawn crop. As an example of the first use it can be seen that the 1955 check does not deviate dangerously from the average; the fawn crop is normals; the next two year classes are a little below average, and the next two are a little above average. As an example of the second use, it can be seen that the 1952 fawn crop was and still is above average (29.4% compared to 25.2% in 1953: 31.2% compared to 26.1% in 1954, and 17.3% compared to 14.7% in 1955). No other fawn crop in the table was this strong. There is some indication in the table that the 1955 fawn crop is a fair one, but it still has to go through its first winter. At the time of writing, this winter has started with low temperatures and deep snow almost a month earlier than usual. The tying-in of game check station data with snow station data is plainly forseeable. In the next few years we will be able to say what constitutes a hard, ordinary or good winter and forecast its effect on the coming autumn’s hunting season on the basis of past game checks. These two features, Be : rin } gf's 0. LIB agin of ‘bisbas oy a@teed Lf ) As #i3seyv 11? .sotadxedak. xieds pe overs y it efi to yevite B dod Deeiaeeee i? avoxsg of wreagons: Jeb of DMISTEge Zhe cas S sismen! oi + bofaovue S6vrny , Sev. ' atid adT ie bys +6 fo BSSSELi¥Yns ean alent of BBS #igeiiay = ; bruce ie Jnomstivpe: tart? offs ec Be ee ye BIBb *tetesy ms c enin aisiuniosa seine sag ow tl «sé fo om sot etaad Pai coups ms od. lity ees aqo1s swt velo vbserls uve eset? tits 4 a OTD ‘ 1 aD | VHS to oe eer b gon eso0b w~aado 7 a ph i? Jada nese ed neo? z siaee ‘Ory fwei off a6" edz mor? i 1oVs | bm od; B yout & wos lovil 8 e718 Bore (.285) Ditooee sAv.To slonsx se eA ,onetave eveds ¢ evode ai {fice baz sew qovo owe? SeC@l ond gene nee + botsqnos RSL + FACr 7 beraqaion a torlto ¢ -(2@eC at 2\,dl ot beteqmes RE, Yi ames nof/solhai smoe at exeit .200tde elds eeu eee edd of fiite vf og z . frsi £ Li } wif il ws! teOL on? tend fe ititw Io. emtt sdo JA .4edniw Saale eee ap . bas esivgdereqaad acl ijiw begiste ead -loyay dedt yiivae Age ' ya 7 bad ~vtw C wore difw p3sh nobdvsde Hoods smee to itesgatys Ww BISeY wet dxen odd al Loldsséadot vinisiq ef boca to yisntbro »hish s neduytien 09 jedi Yau’ os fitnud eines antmos eft no dootts edt Jano LSe7IeBeT ows saedT »adoads ome Prins: to INO P combined with spot checks on browse and health conditions, will place us in a good position to manage the Western Region deer hunt with assurance. Our Western Region staff will realize that all the aforementioned techniques are now firmly within our experience. The remaining essential is the patience to gather a “few more years" data on which to base our judgements. / == - {fiw ,enoidibaos fileed bas eeword mo. eddens goge date ot 43 tg “9g a,% * 2 > ‘| J nesb aviged nyeseeW oft oyanem Of #oteteog Deeg san | | | SS oeBaueNE oH2 {ff sed’ setiaes [ttw tists notsod Kise oW ~50- . sonstreqxe ‘sro nidstw ylnilt wom ere eeupladées Benpigne S1on wei" sa sedisy od soneideq eit at Tatvdgess geintem | sicouegbul two esed of dokdw ao adas FL OS A TT TT $ : i hive Avy ’ Pa S4 Pe ln o hy y i rt %, Pt), j 1) M4 cr ' a" mn aA “O¢ Cee (art tr 4, ‘ia Jeena ras ss eae STRUCTURE OF THE DEER HERD IN WESTERN REGION by R. Boultbee Recently a paper to members of the staff of Western Region summarized the data of three consecutive years’ game check stations on the deer hunt. The three years’ data were averaged as follows in a percentage form; Age Class Average 1953-54-55 F 19.4 te Aor 33 Live? i 510 Se e 68 2.6 Ki ap ry Os of 0:0 Total 100.0 The averages serve as a standard with which to compare any one year’s figures. After nine or ten years the averages should become quite reliable, and should represent normal conditions. It should be kept clearly in mind, however, that the averages represent an average sample of the deer kill. They are not a representative sample of the deer population. Nevertheless common sense tells us that the “kill figures have a reasonably close relation to the herd as a whole. It is the purpose of this paper to work out some of the relationships between the average kill percentages and the percentages of a “normal” deer herd. Since the average “kill” percentages will in time include hard, ordinary and easy winters, it is reasonable to assume that they represent “middle of the road” or *‘normal" conditions. This is proper since we want a standard that we can work up or down from according to current conditions. Similarly, if we can draw conclusions from the “kill” figures about the herd as a whole, the latter will also represent a “middle of the road" or normal herd. 4 7 ae Pai, fea | ; a in } A wie te NOLOGA ViAHTEAW MX OEM NAST MAT GO eAUT aa au “¢ / i . J vd cai iit, esdtived vA Be vii iy bar ts ‘wu ie iy =% , ao th j : . . y - misteW to Tisse edd to etedmem o¢ isqeq 6 yisieoed _ eNe3 ‘BIissy svisguceanoo sarit Yo acteb-etd hes ivem aah." eal | — 1 erow SIBD ‘ersey cers eff .dnwd tesh eft Ae meeeee chrrOL eRsiiteoteg « nk awolket aan : » & ul Ane AA wt AOl anwar «pf Sh at ion fcr 1 OST TA ot doftdw cdiw s9¥ 183 To enin 19SiA .estugit a gsy 910 - vivone fis ,eldstfe: etiup emooed bivote we t a eanotithbnos Lem ‘ont _ a, Jéic/ , evewod ,baim at yluseio sqed ed 6 -: ~-Litnh teeb els to elqnge SAS1SVB M6 Jasesiqey & fo reelugqog Toeahn end 10 olqmse ev issinsaetqet Ba sexsvalt “f{fil edt gary ey elfed sense poses a -Slomw 8 e8 bred oft of sOfdeiog eeolo yLdsiio mGe Juo Atow oF teqsq eldt to esoqiva mr tas esusvasoreq [fit ometeve edd meewsed aq: aoe -brsd toeb “{Lemyon*® g to ORB IMG: > omid at ftw eegsdneoteq "LLB" exsreve Sdd os) £ slosaoese1 ef 3 se edatw yese bas yisatito .6 10 “bso ad? to efbbia® tnerergex yeds Jen 5 Jusw ew eonte resge1q ef etdT .enmols ibaa oF aaibrooos mort owob so qu Agow neo ew da enolerlonos wath neo ow ti ~viaaltmke -enoitt bac ' ,.Slonw 8 o8 bred edt tuods serait “MEDEA 10 "beot eft lo sfbbim” s tnseerges coals beh ies) on r : i) { i mt? « Foresters will recognize the comparison of a "normal" herd with a "normal" forest. Mr. Cringan employs the comparison on Page 29 of Fish and Wildlife Management Report Number 25. A normal forest is considered difficult to obtain but it appears to the writer that a deer herd would approach a "normal" state if it went through several similar seasons in succession. Under such stable living and mortality conditions, a normal herd should assume the following characteristics: 1. The older the age class the smaller its numbers would be, until a zero point would be reached. 2 Conversely, the younger the age class the larger its numbers would be. 3. The fawn crop would be the largest age class in numbers. Theoretically, if all seasons were identical, the fawn crop would be the same in numbers each year, but this is a rather artificial requirement. It may be asked what is the use of a concept that can not be expected to occur in practice. The answer is that such a concept derived from a number of years’ data is an accurate estimate of the Region's average deer potential. Over a number of years, if hunting pressure is properly managed, the herd would increase and decrease around an average condition represented by the concept of the "normal" herd. Wildlife workers will have most contact with kill data. It is important to visualize the herd from which the kill is obtained. The kill and the actual herd can be compared to the two sides of one coin. It is necessary to use the kill data to infer the state of the actual herd and this is where the “normal” herd concept is useful. Some of the calculations given below may be tedious but the conclusions are clear. Probably the best way to derive the "normal" herd proportions is to make a graph of the average kill percentages. This is done in Figure l. i p to noe lisqmoo sd? es LaBOR ox fifw niotesto? ar a ut o e Soe. mpani:xd .1M .deen0? “[emron” gs Adiw bred kai xn nemeysas otf fbLiW bas deft To OS pr no noe tt 9 yorlith berebtenes ef testo Larnro: A .2S sedawil grog fuel sseb a. teddt r9stiew edd od € Bog! is tk dud akarde 6 Ieceves dnuotdt gnow sk Lk edade “Snorron” 2 dosonqgs bf tyii sf{dave dowe tenn emolseeooue mk enoeseé tel ait emveas bluorc bed Lemon s ,adotebbaos vs tlegrom | seo tra tredos nad ) gniwol, _ f LLOW > IScim ' Tf. Sis : cous £4 eae eis aehto eat * fy pe"T } 4 F OW J ij r 0" OWES B Lisay ” : a) { Tan Ts! § , & 7B: Ah « 7 t. nf LOY ad + ,vlortev - y .°od bloow earsdmua } az) ; 6 s2*ted y fLE pet« “Ss Je8ents ofg ed bistow gov WS a mei sit ,isordnepe WwW BmOeKeR 4 ie if (Lies heres es etdy jud yvesy dose stodmun ob emee add ed BENE nemo rivpoy I[aetariicam tt oA 8% 8 ek - } % a tsd3 gqogoroo. s 1 ut eft 2 siiw hedes od yam’ dt. af xewens eT .ooktosiq ni 1990 OF Desomae oo . e} etssy lo asdmun sp mort be ab Jqooseo B Adres” wisitussgog teeb oxys’ ; einotaeh! efd to atpmisee 9 YLTHqo wg ¢ stvwesetq satdoun Th .eieey Be ‘tode 8 is bawors aesotoob bas sesetont iLuow bisd es. aba GaI2I109 vd botheeetqen notstbaos, @ or ei . < Lid doiw tosdnoo seom oved ILiw exevow sStoipiiw = edz dotriw wort hued edd osiisvety of dnagtoamh Biase ed. weno bred Ieucos ' bne Llin eff ~bantssdoy ot wraeeooan ef df .ntoo eno 36 eeble ows odd of bred ([gutos adi to esece edt teint of Beep eivteey af tdasoros bred “Lemon” eng haiad he od vse woled nevin snotdefvefes eft 16 amo t+ yidedorT ‘aheds 915 enoleulones opm? bal Ss 94am oF al anofiao jorq Dred “ Saoron™ ons evin : bit ro enod ef erdi -soystneored LLIs ONLI OVE, eat ms ie ee FIGURE 1 P40 = LG Cc e 30 n t O i Oo 20 O ci fo) H EL. 20 i 10) d 10) O O 0 tt tt tt ti 2 Ti 2k) 8A a: a a Age Class The dots on the right hand side form a descending line which fits in with the idea of a normal herd, but the first three dots on the left certainly do not give this impression at first glance. The seasons covered by these first three dots may have separated from average, but they also convey a strong impression of selection on the part of hunters. There appears to be a tendency to shoot fewer fawns, and to concentrate on animals 24 years old. As information is gathered in years to come, this idea of selective hunting may be confirmed or disproved. At present it seems probable. If.it is true, then it can be said that this aspect of the hunt is a good conservation measure. If hunters prefer not to shoot fawns, then it follows that fawns constitute a larger proportion of the herd, than indicated by figure one. Similarly, if hunters prefer 2% year old deer, it follows that they occupy a smaller proportion of the herd than figure one shows. With these thoughts in mind, the writer has drawn a line through the dots of the average kill, intending it to show the proportions of the "normal" herd in Western Region. See Figure 2, t mm gnibdcesesb & mrct obte bash saotu ede ge seen oAT % a ei! god ,brsd Lpirron p to sobl edd dodw BE eatt ito: idft ovis ton ob" vinisties ttel eit me Bron. itt sranid vd beravoeo Pitoe aes x1T .aonets Gatks tes Lee vets sud ,eqetevs no’'t bovetaqes sever “Yan evob. vn Mrsq cig m0 holtooLee to acicestqmt yaotze 8° We st Joona o% yonobaed 8 od od expeqgs stent cA | s bio PTSSY &S afeatie © Fepdanee og to gobi elds yomoo od argsy af betetteg 2 thoeotg tA . bevorge kh to bemtitaos ad yam 3 Su tsd¢ bise od nao 35 oedt .eatd et gas old do -oIvesem nolssyvreanoo boos S ‘et tant 7 Jt tons ,enwe) toone OF gon RA Sg: 2 sig ‘Lo aortreqerq tegtal B eters erotjnud th ,yiaelimle eno save te wo 8 YIVooo yedst Jgadt ewol for A eyode of0 stugit abddt bisd: te onfl's gweab esd tedbaw eda btm ¢ nt B wode of tf satbnegat aT Lin as eve ve Oo 2 -tolgeh mroteeW nt bred “Lemon er we FIGURE 2 > Ae) e hi C ee 20 n t i oO HS 10 ic ts m9 3 13 23 34 4 53 6p. 7% 83 93 Age Class The curve has the necessary properties for a “normal” herd. The fawn crop in the largest age class (almost a third of the herd) and succeeding age classes are smaller. For those readers who are arithmetically minded it can be shown that the line passes very close to the averages obtained by grouping the dots in threes. For instance, the first three dots average 23.6 (19.4 plus 25.2 plus 26.1 divided by 3). The line passes through the 14 year age class at 23.2 which fis very close to 23.6. The line passes just as close to the other dots if grouped in threes. In this respect, the line is consistent with the original data. It is also consistent in another respect since if the values for the line at each age class are added up they will be found to total 100 percent, the same as the original data. The line for the “normal herd of the Western Region is tabulated below. It should be remembered that the figures, like the kill data, only represent proportions expressed percentically. We are not yet ready to say what the total numbers of the herd are, though such an estimate may come in time. It should also be kept in mind that the table is based on only three years’ data, and will be much more accurate when several more years’ data are incorporated. This paper is really an assessment of the work done to date. en eng po } x ~aaanle fa — ee rm = ete ey ee ete ee ere ee: we Ss. a ok ce 6. et OR eoald “Inmton" s 101 eeliteqorg yrsessoem said een erase oft. btint a Bp) esslo ons teousel fe af Goto. Iwan & 10% fase O18 ooersio exes yatbssdove bas ve twos od nso tf Bobnim ¢f [sottomddtine ome odw Bt rc bovkptde gow reve of ot oRofo ViIev &onesg £ ak. sets d ttt As socstear 101 .BgetTds HE eso elE ya I fb £,38 aniq StS eufq deCL) O.€S Som die SES) os eepio ous aney &f odd davosds coved SAT | 10Ol9 28 Jewt eoeebq eatl sft .O.tS oae Pi mit io ,dosqest erdd wl .eestdd ni 5 Bttr Soetetanos oela ef af csteab ftaaisiao eds dd 4 ises to ontl odd F67 eoulsy ait tf sonte soegse" | tndos ov baunt od (ftw yedd qu babbs ¢« sich leatgito oft es ouse sxoJeeW aft to Biot “femtonl ada 107, gibt ae iit seh¢ berxedmainey ed bh lrorde I wotnd be sai ororee tovesiqes Yina .BgBb eB oid Jstw yee oc ybeet Jey Jom S48 ew sv itso beim 0 pee cs tose davods ,eta Bred ers {dst ont deft button af sqed sd opis Bie piece ioum ed [fiw bos ,edeb taxRey geld etitT bed wigs fpr “18 Btéb tersey stom Len sosnb ot snob avow ons To —— | Mid - 15 - Age Class Normal Herd Percentage 2 30.4 le opt 33 1Z¢h hs Lar 38 Lek 63 26 le iy 5 83 0.6 95 0.0 Total 100.0 « @f[ = ene tooaxad. bral SL LAS A GAT AO ep } LEntoi, > fu We * Ira. bm bs (OO * on ‘ tv % \e \ ia Py i ‘ +a ‘“ ‘ A ° > ov . © " a e IORMt. on > Oia Be a Y ‘ a 1 u f 1, rs ein v own 1 wi > me ES em RECUPERATIVE POWERS OF WESTERN REGION DEER HERD by R. Boultbee Two papers preceding this one have assessed the Western Region Deer Checking Station which has been operated for three successive seasons to date. The first paper averaged the data of all three check stations and established a standard to judge the meaning of data from future stations. The second paper used the check station data to estimate the inward proportions of the Western Region Deer Herd under stable living and mortality condi- tions. The present paper is intended to show how many seasons are required by the so-called "normal" herd of Western Region to recover a condition reasonably close to normal after a setback. A herd is subject to many kinds of setback. In a study of this kind it is necessary to choose a setback that lends itself to calculations, though it may not occur naturally in the chosen form. The setback chosen in this study is the loss of an entire fawn crop, without losses in the other age classes. This would be a very serious setback. A study of how the herd acts after sucn a setback should help us to judge what will happen under other situations. The proportions of the normal deer herd in Western Region were shown in the second paper to be as given in Table I. The third column is a new feature and shows the percentage of each age class that survives to the next year. For instance, the 24 year age class will be reduced from 17.5% of the herd to 12.1% at 34 years, a survival of 69.1%. TABLE I Age Class Per Centor Herd ourvival Rate in Per Cent 2 30-4 76.3 13 2302 750k a3 ae 69.1 32 Led 63.6 he ad | wiat 22 Lok 59.1 63 2a Ey ade le: damon LOO 83 0.6 ore 92 0.0 100.0 If a fawn crop is wiped out there will be a “zero age Class which will take nine seasons to move through the herd and disappear. It may be assumed that normal proportions would be resumed soon after the zero age class disappears in the tenth w OL GAGH AVAG MOross wasTesw 10 8 agmnrod emai qd : ssqdiuod .f ars JeoW eds Deeseans sVad ono, Bind satbesexq et owl servis 161 Dedpveqe need ead dtotntw sofssse ga tagene be) Busah shiv DASE. 43V Yeqag Tak Lm ont seteb oOo? efiosse8 birt, ot bishbaege B bendetidstse bree snolisace aseno bse eqesq bsoses SAT ,.shottege saucy mor? age ae [t-to e110 $7040 focal oid otentias oc sésk notiace ¢ #ibnoo yIELetio bob matvil sidate ¢ebau biek t i rey : > Ee fa} . mi we ea) r Le be toad 8 ™ saris EVE 1 i yt > \ (ta OfIOS + d i bry WwW ee was a eJiveen bisow etede Leaarren peng 198! ond If ese ago Sw peessio ons ‘setdt To aibaud eto Re Dagger a, foo ott .aeaealo ons sound % on ana iofsyorid atevaqee twota ef Gora’ iwsl- quo bionea edd mt ~neqqs eenesifo sus : b' £ qy Inutooent ong idoftave ' vot bevuessy onslivind 6 et aids niags avin ots Tl eidet to eseb eae veov" vobru Amu Loo sdT° Veron age vd ittbnoo ats ef brs sisgddee io beyiwv en awode 8i gets twe Sige 1315 e965 ctos A tuotstiw Bey vetht ond gg C} eony OF Yleaolo Ptogegiies OF hebaas ere moeqgo“ry anv 3s SAT Neos od ms9° oe bra ,“oias tex" 16 sacnd ot stole ogoTg biswil learver asi tavooeT nap aaa faniod oc balte idee” a “ehie a (I .omt s base ang tedd Biss ed mes 2h Gane es mest eft nedw Sey ieee adie a " ' ov i. uy o | e O° oe Lo v rodg ef teqgeq ekdid Be note vi ‘On aod Yoou fimo bus | OLY (Scie € Is*qebhs bas aOR ty lOn BAS 4 15Vv8 lo aelxes so Jenga sied 4 6B bis cadélionoqe’se Aieaos Y anidiag esenld ,doOldabstq sam | o bivow pted odd soltootg t ctste L[eunon eid hwo $8 si. sl sham notaqewees teit . . TS9Y 9vEt 3 seedit odd: > i.‘ if Sava «no regtoqot te il ar , TOI BOW PABTevVs ¥ Oo ds stom od Bbivow. seword ergo ait e@ es be Jepeel’ OIew oT TUBE im to seer ot dade xeelo, ef Ff out connt' As edurees shed et w+oaddes wo: 1oinaqdxe oe of Yisdeanen mri ‘st A further assumption was made in applying the inward proportions of a normal herd to the one hundred deer of Table II. These proportions were not intended to apply to total numbers but it was necessary to use them in this manner to arrive readily at the percentages of Table III. It will be noted in Table II that the herd never increased its numbers after being reduced to about seventy in numbers. This is an artificial state caused by using data for the normal herd which by definition is stable in numbers. This does not prevent us from using the recovery period of three to five years as a basis to work from, but it does point up the need for us to find some means of estimating the actual numbers of the deer herd. This has been attempted with certain big game animals and there is no doubt that we can develop such a step with the deer herd if we try. It is not necessary to develop the subject of recupera- tive powers further but if any reader is interested in arithmetic he may wish to construct Table II for himself. This was done by first constructing a similar table for individual age classes and then grouping them as in Table II. The survival rates of Table I are needed for this step. The fawn crop for each year is found by totalling the adults for the previous year and allowing them fawns at the rate of 30.4 for every 69.6 adults. Anyone who wants to follow the subject can have a copy of the writer's tables by writing for it. : bh ‘ a ba tewils Stig —Paate & ir 4. Gs BQ: Foes . ; erpe t oD + s. Fi j x ahi an Rie i ) ui C Ph eot ) nap ree co Li Nea SVitris 7 ~~ of tt Bs a id s2 . ‘4 i. . GS Oo. DESDE ’ * * a - , — rs Ree 4 £ etas “EO nesy evolvety, ota 0% edfube od? § sid to yYqoo 2 e¥Bd HAS: sschGaneal O"0DT OH00T @GOL Sa"g@Or™” O°OOT OD O7O0E STVLOL P9l. os SG SMBs go gto) er eee Bley 2002 Get SEG - GT Le oeitode mame, Cri Cay SS Ook. oe ee S°8S a Ot e 1 wtsceoW odd to segpdmeoteq ~ Cw ‘stn cs j ase: vizis [159 [> 996. IBY f i Gold 50: TI “OUgE bed LO rey. $$, old Sbn rf / i ¥ f is, oe: 4 ig 3 te . y doso Jeol [3 sey | ant? to dase fa, a 6 = ‘thleths oy erent Oh Geta y LBIIOM SSBBLY BSA bre be a a er temo + rte = ) 2 rr -_ oe sh: fo) YO ah 4 S ft £ “ys a) € . S Y, A oa ane 4 hak ~* ? bd - > s i _* waa . +. ak’ . 4 2 ~ ‘ g a re é 5 2 ohn ae - _ — oa el we Interest in Table One lies in the fourth column, which shows the distribution of mortality in one year over the various age classes. The total loss in one year is seen to be 30.4 per cent of the herd or roughly one third. It is interes- ting to note that the total loss of 30.4 per cent in one year is identical with the annual recruitment of fawns. It isa necessary condition for a stabilized herd that the annual fawn crop balance the annual mortality. Thus, Table One confirms the figures for the normal herd. The next step is to compare the mortality proportions to those of the living herd to discover what kind of losses can be considered as normal and therefore safe. To make this comparison, we need to place the figures for these two factors on a similar basis. This is best done by placing the two ona one hundred per cent basis as in Table Two. In addition, the final column of Table Two shows the average hunters’ kill for 1953, 1954 and 1955 expressed percentically. The last column was developed in the first paper of this series. TABLE II Age Normal Herd Herd Mortality Hunters’ Kill at 100% Class in Per Cent at 100% Level Level (3 Years? Avge) 2 30.4 2354 19.4 13 2302 Loy? eee £3 A re) 7.8 260k 33 Le dee 5 Lis he ‘fall 10.8 6.2 22 ek 509 3.0 63 2.6 3.6 256 73 a5 340 Lae 84 0.6 230 0.6 100.0% 100.0% 100.0% The information we want is in Table Two but it will be easier to visualize it if put in graph form. In studying the graphs it should be remembered that they only take account of relative shapes. In each graph two curves are compared on an equal footing, whereas if numbers were taken into account annual mortality would be considerably lower than the living herd, and ‘the hunters’? kill would be only a part of the annual mortality. The form of the graphs does not falsify the influences under study but makes them plainer to see. -f- etiaw £09 itxvot ot ak sett pr ofdat at iemaegen eid 1svo tseY eno rit YtiLedrom to cottudixdekb. ont a RS od of nese ai rsev ono mi ae0L Lefod ofT .eeeenio ORs au -meetetal ef 21 .btind eno tide wor to bred eld te caso ts no mk theo teq A.O€. to seol fesod sade sang ston a et 3 .anmest to Jionckoeet Launns eo ddbw Lsoltin met Ieuncea ent seds bred bestifdgze es 101 norgsbnes = edt aernitnoo si0 aidaT .endl sycttaciom [saunms Sad er bred Lenrem ent. os Sf r enotirogorq vtitetron edd otegmoo o¢ @f cess Jhon oft po eseseol to bata asdw wevopekb od Duet uoivyil one oi eras srlemo 288. svotexend bas “Testor etoJost ows seoud rot no ws ft edd esalq of baba SW nem & mo ows sid sntfosigq d stOb Jweed et eit -ciaed efi oA od .nolsibbsa mI .owT oldsT ME en etesd Jas geq feu t? ~ Z z il sot [ito *gtaut ssetove sdf pwods owT efdsT to na autos tes iT ,Vilsotonssreg benwsrqxe CPL bas asives eidt to tegeq teri? edt oF bode SO0L. te [LtH l‘axednsk viilsgton brah a AD oe ee hr ‘ djonvl ‘erssY £) steve Loved M00 L 38 shen fF - [ 1 VS. YekS rie Ve Od = 7 d a v za * 1" e * I ry : f « — . ) Cy s va ; u > at : . AS fee “1 . > Wrnrmnf OfF-31 SYN “ ‘= fonae me ene ts he ee = ~~ ed [Iiw gf sud owl sida? «i ef ong ow notzegae" dd gafybsse ul .m1ot dgety ah Jie An oe, oat 10 Jiuosos eset yino yas gang de mB co bersqmes ots eevind owt gee Boas Layars imyooos otni eves stew suedmnm Tl ssecee ons ,Pyed parvil eds neds tewol ‘yiderehienod a on tasuns add to J¢6q 6 wie ed bisow . tebmus esoneutiat ee vtie let Jon seob an 62S Od yonteig pat 7 = 22 = FIGURE I LO P Wale Living © 30k ie Herd r + Pee Cc ae 20 S e 4 Sirah A A Annual ae Mortality aN ey rea dt bat bi +r Cathe . | Q~ ecaiid™) ~~ 0 et 9 I a a Yc a Age Class Figure 1 compares Herd Mortality to Normal Herd Proportions. The “normal mortality pattern for Western Region appears to be one in which the proportion of young animals is comparatively low, and the proportion of older animals rides consistently high. This conclusion is not positively stated since it is too important to accept on only three years?’ data. However, the tendency is pronounced enough to seem probable. Assuming for the present that it is correct, the key to the management of hunting pressure may be to direct it towards the older animals. It would be wise to gather several more years’ data before giving effect to this principle. It is interesting to think that Nature may have incorporated a conservation measure in its pattern of herd survival and mortality. It is well known that a strong age class shows up throughout its existence in the herd and this is one effect of low mortality in young age classes. It only remains to compare the hunters’ kill to normal mortality. This is done in Figure 2. Assuming for the present that three years’? data are a suitable basis, it appears that the hunters’ kill is notably unfavourable to the normal pattern of conserving the younger age classes. Fawns may be an exception. oi, ee Pomel Veo Oe a Bie eo ee ’ oe 9) ke Oe Ma iy i tne > anivid Iearot bioH a : Lair ‘ieee oe ! yitlesrxe PP i ms ne ~* a . %--- ant aa ma — a he uae MD coat, Pore? WARY ape) gp ae ae, ite on q fi" I on ¢ ' « a eS biel [emwyow ot ytiletxoM breil esreqmeo t occa esi missesW rol miesseq yitleoitom “Lacon” eae ef efemins sayoy ‘to moityodera sd? doitw mi Sia s. a - . ; tr = DPI ETE VESECOG. CON ef HE si;foanon erat 38) Satsey sevds ylno 16 Jqeoss of HBITOGuE Cae scidadow meee oF Mavons he onione tq BE yonshred Ori Se OF VE er eJIO% "Oo? ei Si grad tagnetg ¢ it ebtawod of gsettb og ed yam ene abe anidaud 4 IsSy £ Isvaves ‘tettay od seiw biuow ¢= . anijcotosak el tI. .aiqtonita efi “3 cco oi notisvieenoo B beyatoqroont eved Yam etusan i © ,vetlstaom baa fewivrre dpe to mrecvag £ agit suodgyori? qu ewodte Besio eae RAOISe B ‘2B a it yitletron wol to Jostié eno af BENG Bam payee edd fo “Sone Isnton o¢ [fA ‘suegaud ena eta. ‘hy enbanes a r it Lik 2L iT? * oe ade - . oLsoolLt i or Te } 3 > . af eal ‘ r t \ wr - . : . a a Ors 4 Lb ry ‘ {¢ 3 urs’ FA ,> © a} I rfresntane VILL TOTO! a e , eek Y Ot. : 4 ‘ P As & , Ads ; : Kage , " Ore t: - ‘ } : ope i a” 7 . \ wt ¢) : 77 Nt che K. ’ i cy 7 ea ee i + 1 \ i ae We are fi i : i \, > : ve Be a fhm Chin ds famsohds of eaw erat tad? es tro Fbat ne stew tovirhi sweJwdel Bboe mone sf i ead at ebuier ately 2 - ri b ~ ¢ “ - ot OABI OF DoTttepet ByeBD tim » yodmin off a ik +) iy : A . A 7 - i. 2 ‘ ut ie ae f ed Sr ve | p ; f 396 ent to AOESE HS Mog Bet sip 2a ent i fnmitne edt to 6 abe trode oft setei@el To's bae rovill mesaeM ont mort olgaee iso0 5 < -_ fb gow swel peel odt to rodmun Bp ged? soee T8cmg oo ae sit af ytilesrom Larrron evods. afag @ nojalw od bevslet sd od epseqqe gam io tstuiw ond unttwd sex Isnt Aes g' belistab etoM .toiwdelb eda to asaaee taco o1K enokdibaos ysnusi web base 4 b elfid Lndeahioos Ca eaaw eredte it ondt verisid yidarebiagod es ilo Schwa Sbitaeq t goreser?tib akiT. deel 188% ° tevteeanod yd siffd test To airman aie iiwtaxe soob nailaney VL eng to owe tofim etcw to fxdeth val noon sae Jd J20f oft gutuvh Gowsl et beid oF ; . a, » to oe , “aT , m : L600 + Ct etweat to enmswi Sorted ‘ . B ee Lame e ros ds Suborgs't @ [istenes 4 r . nil + : ; tie 4 £38 S i) 1D , e ROE ty ¢ ri wR? > "si : fq T ' r r : Ic t io ri | Ja do {i f 4 ’ tS} ‘4 ° “+e rey fort ast 104 AC td 73 fisimwed piney add att (cat alt te ‘ : . No al i i & ta Gad re fs \ tf - (te iri oes ' aa 7 soLin ov6 e 20 beead af Bile £4 ee OL B mm oad ‘ foe At b rs a Linve SHIDO | Hots -oLdte NORTH BAY DISTRICT 1® 2®@ 3@ bs L. Nipissi a ipissing Plan Showing ® Distribution of Elk in the North Bay District February 28, 1956. Miles 20 10 0 yi LO bry i ih a :. a 7 re. solsterg, yet Gdaes at uM i gee NORTH BAY DISTRICT Plan Showing Distribution of Deer in the North Bay District, November, 1955. TM up to 2 deer per square mile. BH 2-10 deer per square mile. ES} 10-20 deer per square mile. 20 10 0 20 ~~ nor tudizusgelkd aha vai droll. Ad | ekcel .1sdmevol, -oLim srsupe 19oq 1e8b SF eOlim Stavpea isq ALi Sisupc t9q 1808 ? 4 > ‘ww ve ald = 28 « DEER SEASON IN NORTH BAY DISTRICT, 1955. by C. O». Bartlett Summary of Hunter Success Separate summaries are available for (1) Gravenhurst (2) all stations other than Gravenhurst and (3) all stations. This was necessary to compare statistics obtained this year with those obtained last year at Gravenhurst. In comparing these you will notice that there is very little difference both in the number of resident and non-resident hunters checked and their success, Non-resident hunter success this year is slightly higher this year than last, although with the small number of such hunters checked, it is doubtful if this represents a Significant difference. The statistics gathered at stations located in the North Bay district show that hunter success, especially resident hunter success, was considerably lower than that recorded at Gravenhurst. An examination of the accompanying Table I indicates that two factors are responsible for this. These are (1) Considering casual and local hunters as one group and organized and guided hunters as another, the casual and local hunter group with their low hunter success represent 64 percent of all hunters checked at stations located in the North Bay district. At Gravenhurst they represent only 25 percent of total North Bay hunters checked (2) The low hunter success of the casual and local group checked in the North Bay district. This low success is influenced to some extent by the fact that many hunters in this particular group were not finished hunting for the season when checked. However, it is significant that the number of man-days required for them to bag a deer was roughly the same for both the Gravenhurst and North Bay stations or in the order of thirty man-days. It is significant also that with the variation in the hunter success figures between all hunters checked at Gravenhurst and all hunters checked in the North Bay district, the effort reguired to bag a deer was the same at both places or twenty man-days. As expected the organized and guided hunters as a group were consistently more successful than the local and casual hunter group. Although the success for the local and casual hunter group checked in the North Bay district is low for the reasons indicated above, it and the Gravenhurst figures (which probably represent the maximum) indicates that the over-all success of such hunters lies somewhere between these two extremes of 5 and 20 percent. In no case where more than 100 hunters were checked was the success of the guided and organized hunter group below 20 percent; the average being 24.2 percent. .220L ,TOLNTEIG YAS HTAOW MI WMOEAZE Aaaa ud tteliygd .O'%.9 4, = B99 9Ne ternreyet) ({) rot sldsifevs ots coltrane etataged senoljsaca [Is (€) base Jatenneyei apd? astve enolsase aivtftw «sey efit bentesdo eoiteiteida eitagmos oF Yisseecen @ woy seed? anitzsqnoo nl .Jetuduevet 78 aBey gest ao cana eg ni dtod sonsistiib eftoil vrev ar eteds gad: 989. tient bis betiosto eretnud Jneblesteton fhng Inebieer ritdgife et ta9y elds easgose edad Jasbleet=ton — gl to todmin Ifeme ett delw duveitia .teal obi’ wey ein 34 & edJnseorger ellis Tf iuftedyoh ef sf ~bedosais Brame ' ,eonetstTi Lb sans ef3 ut besgool enotdase se beterden aeoidvetiede eat gnebitee: yiisioeqes ,eecooue tetra ted? wode sobrseth « ts bebtoset ‘ada asi¢ vewol vidsishteneo eaw , 8999. I aids! untynsgmocon end To notderimeaxe GA <« eis stellt .sins i _sidienoqees TS etodost ows se bus quetZ eo es steduud faool bis [evess yates Jiw ah = iscol bas Sseueso ed ,tettions es; niedhis bebt tnes reg 3 ¢nesenqey ezaoon ve totnun wol ‘tiene a yet noto1 ati mc psgssoL enotss: te Js bestoedo ete? jo tneoteq *8 yico Jasae1ges vets Jetuinevet Bau edd to sessovea issaud wol sri (S) bessseds ete sual Pict. efit ~JoftseiLh ved itxoH eds at betloedo Ge ‘tem tedt sost sdt yd tnecxs emoe of Beotiemiink. tat 10" Beaton! berig itt t joa iow quot: teiyotsteg & “eae JBM: TastTTaSte at at gL , TVENOH -beroear oe Sw vyidsvwo:r saw iseb 6 38d oF ment tol betigesd Ss TA ni %0 " ae teaae yes dovroll bos tetudneverD ong oe is) eysb-16m ae eft ai notssirev edi ‘diw deta opts Jamo teas, Jetwrinsvs1) js beooeds evetrud Lis asewded & Jrotie edt .toisvdetbh yad dito ena ae Bexnoem yidewt xo eeoslg ddcd Js sabe hd Baw teem Be qvota 6 ea cisinun bebiig boa besingeye eng beds Ievess bne Lsool eis ned’ Teitepesove er108 Isieso bas {so0l od? tot seeopte ed? mayor ang tol wol si tointebb, xsi idxoH erg a] ' Hoisdw) sovstt setunevard etd bas gf ig rg {is-ievo eid jedd eedsotbail (muemixam ed? . emetdxe ows osoiit neowted svedwemos aeeil si1etat Bredsmut COL asdé stom e'teiw eeso on Al odE tedjaurt hestaggio bac bebiuy. eft To eeeooue sdg- -tneoteg S.A gated..ogetevs eds ;daeo% a Le The results of this year's classification of hunters points out quite conclusively that there is considerable varia- tion in the hunters success of the different hunter groups. Unless checking stations are so situated as to sample each of these groups in the proportions that they exist in the total hunter population, they do not represent the over-all hunter success picture. They may provide an index to success if we assume that the representation of the different hunter groups in the sample is the same every year. An endeavour should be made to locate checking stations in areas where a good sample of each one of the particular hunter groups can be obtained. The emphasis, however, should still remain on obtaining sexes, ages and weights of deer killed and other biological criteria that reflect range conditions. Consideration should also be given to the enforcement and public relations values to be derived from these same locations. «QS i etethiud to molsesitinesio ae! igey eds he! sictaaen: oh -slisv ef{dsrebienos at eteds gadd yloviesLoneg sdiup dias .equots tesa taetettlh: ert to esesoue er)esaud of at to dogs oiqmee ot as beteutiacoe or enotdete antadoedo e Jetot eft nt getxe yes Jadd enotdrogerq edd at equove @s tedhid : (Learev0 eft troeetqet gon ob yeds ,nolzs a ow tt eabsove of xebni ag‘sbivorgd yam yedT semgo ni equorg tednud tnetotith edd to nottatnsretdet ed 2 $y ebsm ad biyode iwovsebas. mA vtaey.vreve emee ott BF a io2é to efguge boos s otorlw anete Al anoiisve gritdoeds § eft .bentsido od nes. eqgnorty ‘tetoul wives eg | Bens ,eoxce soiniatdo mo atenex Llide bivons. =a tedt stvetito Isorgolotd: sorte bas befLtA reeb | tevin od oals bivodce nottevebieno) ,atoittinoo pede bsvtish od o¢ eeulav eaotde ler »ifdoey bas FSnaomeot tot . sbaoLissol ete Pd) ee 2 i 7 if ty id ene r AN ri : oe i i wy fe jo TE a i ra Wire ie bape x. Pa) Ved ee i) wl os Ca we if he | 8 mh al Bas ha ane » Os DEER SEASON - 1955 Summary of Hunter Success District of North Bay - (Total for all stations) 1. Numbers of Hunters Checked ( a) Resident Hunters oweeeeceooanve0eorneoeoe oe oo0e oor © 1960 (b) Non-resident Hunters @¢eo00e2o0eoceeeeoeneeooceoeee Ais (c) Total eceCesceereecoveoeo eee oceoooaeeeonrneove0e0C 8208 2174 2e Numbers of Deer Checked fer one by Resident Hunters oeiddededcdddsses 236 (b) Shot by Non-Resident Hunters eoeeoeoovnoe oe e 0 @ 93 (c) Total @eooveceoeoceoooe ores ooo 77T we oe oe BF Ooo OO oe 29 (a) Percentage Success of Resident Hunters ... 12.0 (b) Percentage Success of Non-resident Hunters eeeeoeoeoeoeoecoeeeeeesee @ 365 (c) Percentage Success of all Hunters weccooee 1561 fon Tota) Manehays Of Hauntings o've'v'c's'c's't ce cenes 6761 Cop Meas HOY Geer veld weeded eee a v'a'e'e's'e « £045 azoooul sears No yeo dtroll to soiatekd (enotgede Ife sot {agoT) + OdO.£ oreo ee PVer eon et aneawe eee v< bape: are" ee : rae es@voeoeevounnewreweeseeoee #te taut suobtaeteson | (a) 25S TE OH CeO HCCC eHORHEHES ees Coeernee evan fete? (2) i. b€s concesdicbhaceees SROCTN SeiPtaee xd tod {8 cvesceese vous BtGueet snebbectanok wd storie ese Pere or Isso? OsSL oe BIOcHWH gHebfeoh to eaeooue osevaedvet Jnobieet=noll to. sesdoue eystneotet ee cev+e*v ec eeew eee ereaeeeeanee -gtegniul - = et vesssees StodnuH fig ‘to sreoov® -snednestet (6 [ONO kescevcusvnusees QOLIAUH To eaters EevoT aie G ie a om e409" Paves SCH oeeeres aves eee es ~Heh- tency eyalanah a DEER SEASON = 1955 Summary of Hunter Success District of North Bay (Hunters checked at Gravenhurst) 1. Numbers of Hunters Checked (a) Resident Hunters eoooeoeoocoovown0ea0e 08009090 © 245 mo) Wiemerceitent Hunters sceacncevcevecvenes L6 (c) Total eeeoveovooedve0gc conven aoaoegeeeonvneoev0eagevnge eooe 9 291 = 2-e Numbers of Deer Checked (3) “hot by Resident Hunters «cccaccccccsace Of (b) Shot by Non-resident Hunters e@ooeo0o0eoe ea 0 (c) Teta. eeoooeoeocoeovoncose coe eooocece @eocvsee @ @€0 @ 3. Success (a) Percentage Success of Resident Hunters.. 264) (b) Percentage Success of Non-resident Hunters eosvneooeecee e080 5he3 (c) Percentage Success of all Hunters eeseee 30.6 ta) (Total -Manedays oof Hunting «cccaveoeciaese 1792 (e) Man=Days per deer ecev0eeoevrese0ee2e eo ob eoeeo 2062 a i” a 4 ah as , : i Yay Phys 4 GAGs yy | iY oh, % Vite uh f YP Ca ‘| i “alae QOL + KORAMS Aaa Beo00Ne, toca To vremwe vai dexouv to totwwert (terete evex) Js bedooto stedast): | jeoloed)” atestoul To este CUS coceeesesevbencsccssases BIOCN Siehigeh anus Ou teem eee secenceseons BOW Jnehbigetenoh (Gey Les WOVItrerrrrrvrT TY rr Ce (ok by wo edo NO sew oseeseesceses St00NU Snebleeh ya Joue 2S ewceessenes OvOCHUH Jnebtestaaol yd gone: C3 Coe eere en seeeseepeeneheuseeeeee nen fatoT £sOS . SiatnuH JInebieei to eesoove saedasoued) Jaebiest=ae To nnaceny ensvaeored t . a: Rese es@enrnepeenaeesas etetaut a , me O.0€ seoces Oxstaul Ifs to cosoaut, ogadtionned | Lev eee Bee oH eee ee oricali to ayedens™ Lego? | $08 POSE HBO ORR HHO HOE D X6eb t9q 8 ee) 4 ae if f J ony : i Gd BA yey . on 7 , tit "i ; vee | oO?) i uP Ni ia 7 aD j 1 ai i vat id | « 32 « DEER SEASON - 1955 Summary of Hunter Success District of North Bay (Stations other than Gravenhurst) 1. Numbers of Hunters Checked (a) (b) Resident Hunters eooosoocoeg oo oeeoese@eeoeeeee ee NeteresiGen, HUNLSCYS sesecetsecdessbeeoces Total ooeotcovooevovo0egeeeoeoovoovoegegeoecoeoaoveoovoegeee 2809 2e Numbers of Deer Checked (a) (b) (c) 3. Success Shot by Resident Hunters eeceooeoen0osc ee ote Shot by Non-resident Hunters cecccecccees Total eoogoooeooece@sooo0oe0egngego t¢@eooe#0e0e2070005809099 Percentage Success of Resident Hunters .. Percentage Success of Non-resident HunterS ceccccsecevers Percentage Success of all Hunters .wocacocee Total Man=Days of Hunting @eeooevgnv0eooev0000808 Man-Days per deer eoseoco@eeceeoevooo ee oe oeooeo8e 0 L/i3 168 1883 Seana 172 68 240 10.0 LO. 5 Léa? 4970 20.7 (sewedreverD nats veto etiottede) OUR eee ee ee ee sSaxetmh thebiesh - (a) , SOC ewes ee saeaenaen evyodin: | nbbbaee “ sore - eevetoeveces GTSUMUH Jasblesteiol vo tome PRP SHOE EH HHTH TESTE EHRHEOB SO FREESE Lado? f(s Ai] | Gee) an (BROE — LOBATe. ANT see0one seeigh. to yreomge - ei dtvo# to totavaid ee ee ee eto ont: triehios enol (d) COPS TOKRTH HHH THC OES OA OO De ee ee ee «« LeaoT (2). 2. bs 0 ies rae bie F ‘pe of i 5 J +» atecaui snobiee to ees xe spednesgem trehteou=noll 2o, Seooott sae @ePe tote owavgs ersinaul esveoess OtoscawH Ife “hove jones ogsdaennet 4 ocedetcencctende -igaun son exsdeast save CRRA OH HOKE OE RH ROHS EEE goed inte -~ 33 - TABLE I - A comparison of the hunter success of (a) organized and guided hunters and (b) local and casual hunters (i) represented in a sample of 1824 resident hunters checked at Gravenhurst and at checking stations located in the North Bay district, November, 1955. Location of Station Cooks Mills Highway 64 Highway 63 Others (i) Gravenhurst TOTAL Cooks Mills Highway 6) Highway 63 Others (Z) Gravenhurst TOTAL Total Hunters 2 171 L6 Ail 143 724 487 249 302 io 49 1100 Total Hunter _Days_ 1490 821 117 23h 897 2559 497 344 390 66 293 1590 Total Deer 80 he Arnprior, Sudbury, Lindsay district Hunter-days Per Deer 18.6 19.5 46.8 18.7 20.4 38.2 28.6 3205 2200 29.3 31.8 Percent Success 2347 24.6 18.5 33.6 262 207 48 4.0 203 20.4 hed sit eatin (s) to eesonue tetaued arit To ' >A atovnnl Isueso bas LIsoolf {d) bas etectaud bebt bas eretnur trebiest ASSL ‘to elqmes 6 at besnveerqet |! enoliese anintosido te bras ge pene} ts beslsede ral Inco red easooue — 2 eee Ve€s 3 s AS ayseb=tec7aul teo! ted 6,8. istoT oo a [s3toT isa] «eyed 86 eed 08 OPAL Vee Ss £s8 IVI Vit Oa e vE5 vs oA Tor Est eyL Cree AST el Tes TS, Sl Ae CAS Si OPE Soe € 30 él OL ges ~ &a O2 OWL OOLL sointerh yeubatd .yivdbus , 16 7 At > 7 » « a 4 4 Ss 4 ra ao ’ = 3 4 : ¥ D4 a . PY bee 7 . -— a Age Class Distribution In addition to an age class summary for all North Bay deer checked (341) we have included summaries of age classes represented in samples obtained at Gravenhurst and stations other than Gravenhurst which includes those located in the North Bay district, Arnprior, Sudbury and Lindsay districts. In the overall classification for the district a shortage of animals in the 14 year old class is indicated for both bucks and does. It is somewhat more pronounced for does. Although the samples are small, this shortage of animals in the 14 year old class is evident in both the Gravenhurst and Cooks Mills samples (Table II). Deer from the Martin River area, Temagami and other points north are represented in the Cooks Mills sample. They suggest a more than normal mortality in the 1954 fawn class. This shortage of 14 year old class is not apparent in the samples obtained in the southeastern and south- western portions of the district adjoining the French and Mattawa Rivers (classified as others in Table II). A more thorough analysis of the data by townships and an analysis of snow conditions in the district during the winter of 1954-55 should help to isolate the factors responsible for this increased mortality. Last year the 43 year old age class was not represented in our sample of 82 deer checked at Gravenhurst. The shortage of animals in this particular year class is reflected again this .. by the shortage of 55 year old deer in our sample. Only 2 of the 197 adult deer aged were in this age class. We would like very much to check back through previous samples of North Bay deer checked at Gravenhurst to see if the shortage of this year class is evident in the age class distribu- tion of deer sampled in the period from 1950 to 1953 inclusive. ve ae a Rie Pas he? See dtrot [fs tot yvasmmve easlo-ets ap ot aotetbbe al ° 2oeeklo Sys to esiyssmye bebylont ovan ew (18€) bedoero resem sedjo enotiets bas terudmevei) ge bentetdo scliqmae at besnegay yes “ito oft nt hetsool geodd esbulont doidw Jeuiiasy, 1) ¢ | etointetbh yeebatl bas ywirudbue ,t0oliqntA , ois s tointerb ort tot nokgpottices{[o Eletsvo sft aie rot bacrofbnt ef eealo blo teey #f oft at efemitns To% .260b rot beoavonora stom tadwemoe ef tI .e0eob base axa sit nt elemtns to esedrode etid ,iisme ose volqmer ena exood tne sJewrinevetd oft déod nt gnebive sit eesio Biow .H21R isvifi arsaeM ods movt teed .{1i oidaT) esiqum good odt nt begnseorqet ets diton séntoq testo Saas ait at ytiisdxom Leoron npdt of6m 8 Jecasvea yenT . 7 , — 1 <) 7 he Eye ~ a“ " os a | 3 . ‘5 : bentdmo) soxvt 3900 stoves he a ee ERI A at TY YE . aneoted to .olf trated Wo, «ov rneorsT = ok ipjoT to. ‘1380 isjoT 10 . seem fajox So € sf ES £ Os sE $.85S {J ett S Oe s€- ah a b OF 4 0,08 T.f £ Aes S oe 0,00L e¢ 0,00L ef 2.ee as y ae os to egA oystteva ‘to epaé ‘siieamh 2.8 eatiubA Ife T.€ Beall a+Lirbh @af .vol xsel’ - norneoe arid, gets neddsnow 20 | nota, | oot don e90b - devd ai sedew To ed og _ Bol goisaun deol egob yosm = oles yas" eeyeab yurstavd boog Ils eaiwiendo ae ba 0 wd begreqeb woae ,.sailontt booy ‘ke ysbeouT tqeoxe eyes rsmusa pose ‘Lh ~ ef , pentemst bas (getont dae): oda yebeaakeW bewo s1308 .vol ao woge eto = © av at deol OBB entrtemeag so dems .tdain yebeembeW bloo bemiwd ,yat a Bt « DEER SEASON 1955 Age-Class Distribution Tove Deer Checked .sewese 252 Se tUEiS cas owesgesens LLOQ Adult Does eevreoceroeeeeace Buck Fawns @eesoo0e0ee@eseenoe@eodst9od2 DOG FAWNS scoscscevsceece Unaged and Unsexed eeeooe District of North Bay (Hunters checked at stations other than Gravenhurst) Percentages of Deer Checked Ragule- Bucks vaveuanes; 542% Adult Does @eoeeoeoe#eoe#eode 29.2% Percentages of Adult Deer in Each Age Class Age Bucks No. of Percent Deer of Total TOCAL PAWNS secasavese 25650 Does Sexes Combined No. of Percent No, of Percent Deer of Total Deer of Total 13 35 36.8 20 1.7 55 3408 23 31 32.6 22 Bed 53 3365 32 21 2251 1h 2202 35 2291 Pe 6 6.3 4 6.3 10 63 54 3 Lek 1 Leb 2 iG 63 72) a3) 53 + 2 192 2 912 3 “9 03) 103) TOTALS 95 100.0 63 99.9 158 99.9 UNAGED 17 15 32 TOTAL 112 78 190 Mecccs 2.6. Aauit'Doos 247 ca tedte $6 stiesisi ‘to /.o% _tneots't rteotey 10: se ftsta?t L-: Oo 49574 Bs io... So a = | a8 Bo Luba fin * ee SA0L HORA saad eis rhe} eee potssdiometct, veoldaogh Yee ate" to torsserg saolgete Js bodoers axe dru} {gestdoevey) mad? tesco borxtsedd .rg9ed to escnsineg ped S2S cavens boxgerd) | ‘ OLL ovecaccepoens BRO BO LAN esses BMOHE qhEnn TS omeeseseeeeege | aS .0S peececesee 8900 CLUBA ; NE ue tneonesae enn i Rew S sevesssees etwr'i Is70T errr? Tor.) e ecesee DSKGAAY, BE _bontdmoy soxsG Te 2208. _ Bx2ue To Bde ee [ Oe et 2.88 ee ~ al eC do. fed >. as .- mm ae) OP L 40 eghk egatovA - 39 « Weights Weights are available for 79 bucks and 48 does. Only 6 of these were obtained at Gravenhurst, with the majority obtained at Crystal Falls (68) and Cooks Mills (46) in the North Bay district. The checking stations set up in the district have a number of advantages over such stations at Gravenhurst in obtaining deer weights. At the local stations more time is available to weigh deer and they are usually transported loose in the vehicle. In comparison there is less time to weigh deer at Gravenhurst, where on busy days there is a large number of hunters waiting to be checked. In a great many cases their deer are either tied securely to the car or covered with camp equipment. We would be very interested in knowing how our weights compare with Parry Sound and Pembroke deer. Violations Ten violations of The Game and Fisheries Act were recorded at the checking stations operated in the North Bay district and charges laid in nine cases. Three hunters were charged with transporting a deer without a tag attached (Section 68, sub-section l(a): Section 65, sub-section 2), three had no licences (Section 7, sub-section 13 Section 11, sub- sections 1 and 4’a’), two were carrying loaded fire-arms in a vehicle (Section 58, sub-section 1'a*), and one hunter was transporting two deer with only one licence (Section 31, sub section 1). This represents roughly one violation for every two hundred hunters checked. The operation of the checking stations was publicized in the local newspapers and many hunters knew where and when the stations were in operation. This, no doubt, helped to prevent a number of violations, although with no information of this available for past years it is not possible to measure this year their overall effect on violation prevention. Comments and Suggestions Many complaints were received concerning the form of this year’s licencee The most common complaint was that the tag attached to the carcass pulled apart when wet and could easily become lost in transportation. We noticed at the checking stations that a great number of tags came off the carcasses when they were handled for weighing, aging, etc. Others complained that they were too bulky and could not be folded to fit in their shirt or pants’ pocket. Some more research work should be done to improve on this year's licence. we ae) A, i : / o « Sith han é e . say fe t i . . hau 4 o oF ~~ ya vinQ .ecob 8 baa adond CY “0% sldelteavg ste eddgiow viirotam edd dtiw ,dewridevs70 ts bentstdo stew vee: took oft at fd) effiM@ exfosd Bnew (80) efiet facdeyr0 78 Pema i ? ii B = ovat dotadeth odt at qu doe enoitete gaidseno eat at detudneves) te enoftste dove revo segecnevbs Tee a: omts arom eastsate Incef off 3A .etdgiow ten Be ‘feveo ote yous Bas iseb datew os eke ab ‘SW OC snot af exert moelsseqnioo nl seo tia lo tedmur ogre s ef otedd eyed yeud ao otodw ,ceTutim terdlj eerso ynem testy 6 ak besdoedo of OF gaits dtiw bevevoo 16 tao oft of ylewoen bods P . & = 409 . t Siew «0 wor 2ntworo ak betseresat yrov ed bigcw eae tesb otordmed bas bavso® yrtel doi 7 row okrodetd bos omed edT to saotveloty sei ysd daxo! eft at botereqge eaotdese gatdtoeds ats 38° stow. atosicd eo? .eogeo sata nt bist sseisdo Baa bodosase asd 8 twoddiw teeb s aalduoqenard aa S noktpoeedue ,20 norsoo@ yla)L mokjose=due —aee edie ,il noitsav®. il aoksoegedue ~.j\ toties®) seoneny B mi amsas ow ffoiiw Iffd oft to siqnée am gee eee oft lo nolsreogmoo yas ond yierdeiioos eisecees bua. 0 vi y" bid 3 rotten 6 oviovakt DiuOw SI owaword ¢ 10 dsinomsl 2% tniLlosb ted3 bis $98 2G @YBeY re OYE ‘Ie yond: pitnont oad iJ0 es8uho mort yotie Eso! 0 onebivo vnsbruds ,isvewod ,el si6enite geum enotisacig ive J o& anoiteeynus osedt Jotbaty - aa é "lS56D J AEDS 1 ob aw d¢add asi: Sdpdorg emesos° el @ib iw xarvow J "LE 1 evolts’ sanity dns soba sBitokas afiveto sfd mort do, owe boters iitoteth eaupo yer dottw exotost odd tou eanoitste antidoens etfs do etotae! LotgyooL notwantoristeb eye me -toob blo bus anvoy neowted ayotvyeted’ sqsapeo TERE -aboitom § mi enotjet2 mailed) oT oO atone to efqmee aobis1 s asedo don ob ow tadd eldieeog: ei. 4 ‘todmin ¢ worl seinre biuoo eid” ,enoisaga yuttoeds edd yd to s0 et liste [ee oF . cre a ot a ered Phin to sonsbtovs. etetediiel ot Lipve Jnomsusgetl fe tw ton bib Pinched ‘> ee ‘gh if asl ) a ; (ee ry on a This is, however, unlikely since any deer is legal game in Ontario and there is no special stigma attached to those killing fawns or does. There is some evidence in certain areas that avoidance of long established checking stations does take place, but this is usually due to unwillingness to “waste time while the deer are being checked and questionnaires filled out. It is unlikely that deer missed in this way are different in age composition to those examined. If the composition of the kill changed as the season progressed distortion might occur if checking was only carried out at one period. In the Western Region checking has been carried out at intervals throughout the long season while in Eastern Ontario the hunters habit of returning on weekends ensures that the weekend checks sample deer killed at all times during the hunt. It seems unlikely that the sample checked on the stations is not a random sample of the kill. Hunter Selection It was mentioned earlier that there is evidence that hunters do not take fawns according to their availability. If hunters also discriminate against yearlings and 23 year old deer the distortion apparent in the kill curves could be accounted for. Discrimination against these young deer implies recognition of age classes in the bush and this raises the question - how? In Ontario yearling bucks average from 30 to 35 lbs. lighter (dressed weight) than those 24 years of age. This with inferior antler development could be used to make distinctions. The differences between 24 and older deer are less apparent. Field studies and conversations with hunters do not indicate any prejudice against taking these young deer and indeed under normal field conditions it would be almost impossible to make distinctions even if the hunters wished to do so. With does selection is even less likely since the average weight difference between yearlings and 23 year olds is only about 12 lbs. (dressed weight). Yet with does the distortion in the kill curve is more marked than in the case of bucks (see Figure 5,D&E). We can probably dismiss hunter selection as a cause of the relatively small size of the yearling and 23 year classes in our checking station sample. Errors in Age Determination The possibility that errors are being made in age determination on the checking stations should not be overlooked. In October 1954, a course was given at Maple at which most of the biologists and wildlife management officers, who were to carry out the work of age determination on the checking stations, were given instruction and a test. The total error for all who took the test was just over 20%. Another course and test given at Tweed in the fall of 1955 gave no better results. The problem of errors in age determination of deer and the soundness of the Severinghaus method was discussed at the Great Lakes Deer meeting held at Lutzen, Minnesota on February 14th, 15th and 16th, 1956. Switzenberg from Michigan displayed some jaws from known age deer killed at Cusino. He felt that 90% to 95% matched up well to Severinghaus’ descriptions. There appeared to be very little variation in wear in 13 and 24 year old deer but after this some overlapping occurred. Occasionally extreme deviations are encountered, one jaw from a tol te a = = ‘obtstnO ‘nk often) Ieeel ek tw ae way ae ; - gmwat gnbisht: seons ot berls sre Boag eonabtove - vids dporn otadyso af eptte iret OW akis vad . 65e8Lq” éist- eeeb endlinge gataloddo | ‘be tech odd efitw emit “esenw” of pesngabll tan 0 yvlonitiw et aI Fo be Iftt cortennsisesip bab oO” aot i feaqmoo ous oi snetebtrhots yw etd? af bese tn end es bounsdo Lfti aid te ioltisogrios ong tt: «Best c cxvens IL swooOo JIAa im cotiuoteth Beeset tse oteoteow ong ‘aL ebolns oq uit ter mt ofircw soesse RAO . tiofsuowde elavie: uf 3B GLO. Pye esiweas ehiaedosw no antarusor Yo aiden etotandt. end qlee of? sotish. 2eortd (fie 28 bolita 4e0b elqita sions brioisaws fiste arts Aang if Vigan areas {fio odd to elasige Mona OL 798 f tiobtve ek stods staid totliss banesonem rial a Les deitayve «i : Ebioces epwst 6 SAB ; Sf r sentass ed ents 15060 o :~'tO ! 0 j : i Lex Ag i ois > l i rj Of £i : THUOYVY os i tente a ~ ff : wWIey ez bis “ce p nq ~@=@di ‘#f c {) yoegt 2 5 BAG antinsey a) {7 BINO daicw 2! pues to vuyvesv €S sg6aa ene (- tio t bo ek in. ofr 1 a i ; ai! res Seu od ro Livor J AOU] ap hs Val y cre ibe NY£LIGS op c “Ee rsblo pas és Neswie coon ' “vas estsotbnt gon ob etosaua Hier elOLdee'ts Viigs Soa ‘lution tsbau boebot DNS “toeR BEOV eae Ag giLhas o 3a : itonisjetb ediem of efdiesoqms, Jeon i od binow of smok evs pi nottootiern esob ANEW Yoo Bios beretw girth enntivssy .asewied Otoreatt th gdartsw SAS IOVS and sorte ¥ dtiw 3oY .(ddstew boreoib) sadl Si seeds vito ef aaa A ens oF vadg bolvem otom ef ovews L0Bl edt ab forsiose ‘podnorl @elmetb yidsdorwg 169 OW (3a 2 vies gi sou) aa inifveacy:-odt to oaie Lien bs foviteles oy to esuso Bee i{quse colivsde aifaseao age he nanag lo” noite, LiMLS zat. aug ai eben anted erp estore dads wiilidtesog a flooireve od Jon bivone a techie uitktoedo edd m6 ff © to teow dotdw ja efosM 36 novia Sew eemes & AtOL io yrreo-o¢ stew ofw BISOETION: ‘remeypaam eIttibiiw ba ‘apyFeotew ,eaoliste nobtoads eid Ao Rotssatemedes aes fee sit Hoos Orw Lise For 4 ents ladgos ofT .teot b B ott ot beowl ta nevin dese Bas Baynes Geneome Bos sas inee't 1e8SJed ON OVE 1g tesh lo soldadloxedeh es6 Mk eaeiae to payee, od eit 3a boeevoeth caw bo pais rig ee on? 10 risuadel ao scoseanih .nexdal ge Bien eens ro bevyelgeib asutioiM mori yrognond ive OLel easol bi jadt sfo'l eK .ontsn) ge belies i906 ags owornl - “sadT .,enoiagizesdl Tens sipat re vse OF. ifew 4 qu Boris: TH8¥ is boas 41 of tsew of notdeitev elsgt. toV yitonotenoo0 vbermis00 gniqgsiteve emos ein 8 mort wat, ana bots taveome., : oe 124 year old doe showed a degree of wear that most workers would have considered fairly typical of a 7. The fact that variation in wear occurs should not destroy the value of age data derived from checking stations provided determinations are carefully made. Mr. Ae P. Boyce of the Michigan Department of Conservation kindly gave the writer some figures relating to errors in age determinations made by some of their staff in 52 tests on 50 deer jaws each. The total error amounted to 22.6%. Table No. 1 gives the numbers in each age class in which the age was over = or under - estimated. TABLE NO. 1 - Errors in Age Determination of Deer Jaws In Michigan Beta eet) Bea. Wlba » ode Jaws aged 9 Total incorrect rf Percentage incorrect Total aged older 4 % aged older Total aged younger % aged younger OO DE HDS LS kK On Wo er Ww > Lo ca Ww ht > ~w It will be seen that the error in yearlings is very small. Indeed there is no excuse for mistakes with this age class for there are so many excellent diagnostic characters available. It is extremely unlikely that the apparent scarcity of yearlings in our kill curves is due to errors in age determination. Two types of error stand out in these Michigan tests both of which would have a profound effect on the composition of a kill curve. Firstly, there was a tendency to place many deer with wear characteristics of 23 year olds in the 34 year class. This error amounted to 18% which is a very considerable proportion of this age class. The effect of this error on a kill curve would be to pull down the total percentage of the 24 year class and boost the size of the 34 group. This would affect the relative positions of the 24, 34 and 43 year groups in the kind of kill curve plots appearing in Figures 2, 3 and 4. If the right correction was applied to any of the kill curves for eastern Ontario and to those for 1954 and 1955 for the Western Region the 23, 34 and 44 age classes would appear in the plots very nearly in a straight line. The Western Region kill curves appearing in Figures No. 3 and 4 differ very greatly from those of eastern Ontario and provide a most interesting illustration of the use that can be made of this type of data. Mr. R. C. Passmore’s studies (1) in the Western Region indicated that the year classes of 1949 and 1950, (i.e. the deer fawned in those years) had suffered severe mortality bivew etedtow seom tary “show Ye Sona AN 3 To Laos yortes® Jon blyorle .aniusos9 rpem nd, Aokdgh ey ye apa» bebivotg .enoltede antdoeds movt bevineb agah: | shea vilvie tm ots” ‘eno8 nolssyroenon ‘to 29 "18q© I apy tdo kM eld to sovol «4 sh ie an ni eon ¢ antsehon eormumit omoe.19tirw ede v8. 1620 U2 tx ea o2 At ‘tete beds to emion yd Coban enol sam © ag s aa A? ; % ‘JT POOLS 6 TTS [g2o3 ont dofry at eeslo ous dose mi exodaen ond eovin 1 son oldatt | ~hotsmties - Tebny to « evo Be a msatrdotlh ny ewel tos to not taotnmessd ssf Gf Gown ay bs ee OE en a EES A UR a nae Oe ere ee arm = enue nda netenaettingee es entate ee RRS AC ACI V5 f t> fm - ic ic i Ri. alin er) ey — , ° = antes cagibiaids = F , 38 c) Se [2 >) \p Av 790%" ae 20 eter ee eS GE . tosrieomh, § . ea tobLo us er: OF E ef ) rogave x 19% viov el anyaiinsey 1 sorte oft Jead nee eo Lobe seslo ens it nokw fesceio .1ot seyoxs On ek stemd) »eldsitsvse avedsarado eninath tnsllonx Vis eae sanifisey to yélotses daorsage sae salt “veda ~toldantsamedeb oye Af exon OF SUD Bz 62V' tod etesJ trinlM o it A 2 TONED ‘to ee [fir 1o motitkeogmoo : No gos'ts bavoieotg 8 eV, sow fti 1b ynéem essig so +8. “pew ered a fee! oy &€ edd ai ebic 1s0y §8 to etdt to notiteqoertq sidstebienes ov B&B ef dott oF ed bivow ovivo [iit & ie xOLtS | ekdd to sostie ofl Wig daood bons sesios ts9y &S off To Sseetieeree ieso3 atiotstaoq ovisele ij goolte bisow eLe? «GOT tolq syvriro [fiat to baid ed? AE sqpoue wey pos gE gew coftoenrtoes ‘te ae ee ou bus. € aor it of baa otfrezc0 ayred < ol foveal Crh ‘ont. to -¥ op wa AE, id nok be r19daow odd rot eee a soit J. isis Dm thks vit: WY VaSvi.3 tole ont ak TH9qG b eervall at anitsoqqs eevins bias Botaen era 8 | ‘sJeso to osodd mort, yitsets vrev tet ty ed moo Jtadt ery oft to notsanieelib gatveowesne | pit TE (f )}) setbuce s*or0EmessT 60 off Po fy BIEL: to: ; ~O2OL baie CACL to goessls 165 ets asrid bospoth viifsdiom eteves bereliwe har te TREX seo, ala on due to depleted winter range and the hard winters of 1949-50 and 1950-51. The 1951 kill curve indicated shortages of these two classes which were then 13 and 24 years old. It will be seen that this hole in the age structure of the population can be followed through 1952, 1954 and 1955 when they reached the ages of 5% and 64. The 1953 kill curve however does not indicate a shortage of 34 and 44 year old deer which one would expect from the information contained in the other years. It will be remembered that this was the first year that the Western Region staff undertook age determination on the checking stations, perhaps errors were made due to inexperience. Variation in Escape Behaviour Between Young and Old Deer One often hears hunters discussing the difficulty of bagging certain very large and presumably old bucks which are occasionally seen, usually when least expected. This implies that wariness acquired by experience could be expected to influence the occurrance of young and old deer in the kill. We have no direct evidence on this point from Ontario but some interesting figures from New York shed some light on this problem. Maguire and Severinghaus (2) drew attention to evidence which they suggest indicates that yearling bucks are less wary than older ones at the beginning of the open season in the Western part of New York State and in the Catskill Mountains. They showed that the average age of bucks shot on the first day of the hunt was significantly lower than it was for those killed during the rest of the season and that the percentage of yearlings in the kill was higher on the first day than during the rest of the season. In the Adirondacks this kill characteristic extended to 2% year old bucks as well and at the same time the percentage of yearlings in the kill declined steadily throughout the season. The kill curves for bucks for these three New York areas for 1946 = 1952 are given in Figure No. 5. The New York situation is not strictly comparable to that in Ontario because a buck law was in force during the years the data under considera- tion were collected. Furthermore, to be legal a buck had to carry antlers at least three inches long. Maguire and Severinghaus point out that in the Adirondacks an appreciable number (53.8% in the 1943 any deer season) of yearlings and even some 24 and 34 year old deer do not qualify as legal bucks under this regulation. They mention range quality and winter severity as the cause. This is not mentioned as being a factor elsewhere in New York. They imply that the distortion apparent in the Adirondack kill curve was due to this high proportion of yearling deer not being legally available to the hunters. While this factor probably has affected the age distribution as suggested, it has also obscured any effect that other factors might have had on the occurrance of yearlings in the kill. ; The Ontario data suggest that an additional unknown factor 1S Operating to reduce the occurrance of yearlings (particularly does) in the kill. While it is possible that there is a change in tojos? owominu aAGRs iihbs ia dads daengue stab oftsanO e cf ’ ‘mi egaenio 6 al oveit daild tenon et af aacin t SaorthaA orfs ak. dasisgde AO Ls yoda lb edt Isat viqmt Yor yidadotqg totost era: iw BT OSMIUM eda oxt oideLinve:t . big 02-040L to eredntw buiad abr bon wunns, ee tetw _ owt ceeds To esgadtore. edso tbat OVID. pig: Li Jad $ node od: (Liw ti ablo- BItRSY éS bas - a stort ee » bewolfot od neo nottsluged edt, to smdoonte pin bus'éé to sags end Bb: dsnex yods mow -8eOl bas AgeL . o Ons: »Jsorbat son Beob tovewod evaeo LLL bec te jJemrotnt edd mort toeqxs bivow ef dolidw wsob blo Geey Bids tsa3 botedmomes: od [i iw Ps 2teoy tengo ae oye daootisbiy Tiede toflyoh otetesW odd dan? ason gee Daim oIsW BYOTIS oqefteq ,enokiede gaidosife eft ma Reman - D9MeLITSGRS! r 4 2 % re | © | ¥ — = =] ; e 2 t im co. ei] . : . 4 # Ae | L i s (Sow JG “Th! As V Set Blot pe] ROBLe iD - Oe A OR ae — om .—_ - - — © a —— . —_——om ¥iLio PT Tick { FS Ai eYoorint ete eis dofdw edtond blo yidsmuasiq bas snus , ra oe . nf ty a a) “| » 4 ¥ , arf VENA Sellar Ee6£A OOO X JeBbol Menw yifeu as fee | sonesultint of badosyxe od bivoo sons incaxe wd bene 8 ‘on evsd oW {itt edd ag 4 Bae arsoy to ¢ Tt gniseersiarl gmoe gud of O mott LOO atid XO 6g ap os ety ) Sdyifl omoy bade areoY weve . q ~~ 7 0 ¢ 7 ' ‘ = co -éntsesnvoM L[f[idets) effi r ive 4 Sasde iO¥ yale mie WEE gserli soft co gone edo to 98S SER TOV ody teia. [{it seodt tot esw df sedd yawol WE JMBDL tingte a exnuri¢vssy to ssssuo! 7 of Sedd boas nhosses ods td i, * +: ah {: Ube | ear) «re tert Th) me ‘tonate 4 bebnetxe oftelyedonyeano Lith etdd exopbaotibA ent euSinootegd ond omit empe odd 38 baie Diew ee sta oe Moesse std trodavoyds yitbesde bettfIoub Fi ome ae Hx0Y woll: setd eadict stot adood rot govars Titi ae ~ ‘ . l10¥ woll, of .c ,oll otwait at nevis ots Stel = sed sevsood ‘otastnd al ters of sidsiaqmoa eisetices Fon esiobienos tebag. szeb j etrey of qcLbrsb goto AL. V2RIses < I$: Sa RS fe AB i690) 9d. .0d ¢ O° TON T: trond ‘ »bowos. eusfuatipve® bis srivgem ogaol estout-so1dt JeBo, 8.f2) 4 i BEd re ye: ea oe bHOTEDA ods at. OB pas #&S omoe move ban epcliggey To, (iemsee teed yas aint tebe eos Lon: if ae viilsup ton ob. 198 ac ysinevee to¢aiw. baa yo tieup eater moLenom ate if ototlwoeloe: totost s gated es Domesenem wen Si aan : OW ¥ ~* a sseb: snifassy to i cogorg did efdt o¢ oub ¢ oels eed tt ,bedéoRuve eB MOLINE LageED ons ote odd ao bed ovsad tdgta etosxest torneo gant sootte 9 Sift ods mE sgniiissy 7 a.) virsivoisyeq) exntfansy to soneiresso ‘end ae 03 aa mea, 4 the frequency of yearlings as the season progresses, they are probably at all times less vulnerable to the gun than older deer. The kill curves from the Western Region of New York and the Catskills are of interest. Their average mortality rates are about 70% and 60% respectively. Hunting pressure in these areas is much heavier than anywhere in Ontario and the harvest of bucks much more thorough. Such high mortality rates can probably be sustained indefinitely as long as the doe component of the herd remains productive. Further evidence on differential vulnerability of some segments of the Ontario herd is provided in the sex ratio data from the checking stations. Table No. 2 gives the sex ratios by age class for 1952 to 1955 for the Province. It is not possible to say at this time to what extent these are truely representative of the actual condition in the herd. Highway kill data suggest that during the rut deer fall victims more frequently than at other times of the year and that bucks are far more vulnerable than does. The hunting season coincides with the rut in most parts of Ontario so that there is a possibility that sexual activity may be a distorting factor in the sex ratios of deer taken by hunters. It will be seen that in the five youngest age classes bucks exceed does in the kill. Beyond the 43 year age class there is an excess of does which becomes progressively more marked with Agee A chi-square test was applied to these figures to determine the significance of the apparent differences. The heavy preponderence of bucks in the yearling class attracts attention. There was a highly significant difference between this ratio and that expected from the whole range of data. Since the 23 year class ratio did not differ significantly from that of fawns one can conclude that the relative scarcity of yearling does was duetoabias in sampling and is not representative of conditions in the herd. There was also a highly significant difference in the ratios of the 5% year class and the 634 age class from the expected ratio. Whether this also is caused by a bias due to bucks acquiring greater wariness than does in old age or whether it is a true reflection of the actual ratio in the herd is uncertain at present. ~- ee 1s youd ,eoeeetR01g Noesee odt a8 agnilissy to yo: saabh tebfo nedt avg odd og eldstenisv seel coms ifs ts brn AroY wel to aolgeA mrodeoW od mort eovio f{bl oAT | sts Bodst ysilesrom oystevs tfedT .desitstat to fap efLrtes, epee seont nt sivesoiq gnidnwh .\¥ls visooqeet rel exoud lo sgaovisd odd bas ofasta0 at oreciwyns oasis teive od yidedotq os9 eodsit yi lesiom dgid rlove sdauorond § brod sit ‘io snonogmoo sob odd es gaol es ylotiatier -ovitoubowg: 08 ‘to ystitdsetonluv Isi¢nerettib no sonshive tenga Bisb ofse1 xee odd af bebivorq ei Hted ofsedad pret: anottsse ane to. Geel x03 eeslo one yd @oldsa: x6e oft eevin S so Se st entt etdd te yee o¢ o{dteeoq ton-et JT “seantvoers oe Isutos Spe to evisatnossrge1 ylouTd of% epoad cer odd antish gadt teoggue sisb Libl yewdg tl sbrod ete sHt To npr te tengo gs nsnig yidwoupett oom engoky te .esob nsds sidsxonivuv stom Ist) 6% edoud ¢ ed1aq teom at sus odd dtiw eebionios. morse pear yitivisos Ifuxee gad¢ yoilidtesoqg, s el sxona: vd sexst tosh to eoldet xoe oft AE NOdaBEy aseesio sas tacgnuey evit ons oft Jedd fees a oft essflo oss wey 4) ofd bunoyosd flit ene oe ifiw bodlism stom dod ieve'inces aumoosd doidw oj so1git seeds o3 boifqqs esw Jegd o7nup eet siT ,esonerettib snetaqqe six To Soneoe ay atosiits eealo gotinsoy ot nt edsud. io somen eltt noowsed comeneltin strsofiingte (inats & esws »683B8b to sans1 oforw ord mort fs eaank vidosortiogte astttb son bib ofss1 eesis assy aS © ee io viforsoe ovidsiet edt sgedy ebuloaoo ago) Sno ovitssnscoiget Joa et bas yatiquse ote ibe ao peed vVidaid s ofls asw sts seslo 938 #0 adit bus eeslo wey 2 ara enid s yd beeuso ei oels eins tose | pce 538 bilo ni e906 nedd esontaew sede bied oft ai ofts1 Isusgeos ond to AoL39. EU ts Maer TABLE NO. 2 = Sex Ratios of Deer by Age Class for Lindsay, Tweed, Pembroke, Parry Sound, North Bay, Sudbury, Manitoulin, Sault Ste. Marie, and the Western Region, for 1952 to 1955 from Checking Station Data. od 29 Ratio Fawnie 166k LLh8 1152100% 1% 1900 1353 1402100 24 1188 1365 1092100 38 1071 883 1212100 id 155 360 1262100 ét “46 ) 119 ) 43100 ) 3 ‘i ; i L6 ) 151 69 ) 266 523100 ) 573100 a S 6900 5886 117:100 % 1954 fawn ratios not available for inclusion. Hunting Methods In Ontario there is one basic difference in the manner in which we hunt deer from the states in the Great Lakes Region. We permit the use of dogs. Hunter opinion and the extent of dog use has been frequently measured in the province. Generally speaking there is a decline in their use and in hunter acceptance of them from east to west. One frequently hears discussion among hunters on the effect the use of dogs has on deer and on the composition of the kill. One sometimes hears of cases where hounds lacking in courage have been chased yelping out of thick cover by a large buck. It is doubtful if this happens often enough to affect the rate of occurrance of large bucks in the bag. Some hunters complain that young deer, particularly fawns are more easily killed with the use of dogs. The kill of fawns has already been mentioned and the evidence concerning yearlings discussed earlier indicates that they also are less vulnerable than older deer in Ontario. There is evidence that this is not so everywhere. In Minnesota, the use of dogs is prohibited. Hunting pressure is very similar to that in eastern Ontario, about 2/3 of the 80,000 square miles in the stateé is open to deer hunting and about 170,000 hunters buy licences. Unlike the other states in the Great Lakes Region they have been shooting “any deer" without restrictions for many years. Four of their field kill curves for 1954 and 1955 have been reproduced in Figure 6. The sexes have been plotted separately. Their data indicate that yearling bucks constituted 45 to 50% of the kill while in Ontario they average about 36%. With yearling does the Minnesota percentages run between 31 and 35% while in Ontario they average about 30%. It is possible that the — , boowT .VSebnil: 1ét ees a. yd tess to NM gipitcnee’ xs& «= § ye Mi cwwwdbus .yed divoll ~bavoe yrisd p+ [ge misdeaw odd bon at ge 2098 eT al ivostast | cel ROO LL - Bat WoL OOL ONE Gc el | OOCL . OL COL GOEL AL OOLlS{S Ff E85 iY [vo \‘g OOL dS Car eed OOLs £8 © irs [iL { OO£sAd ( CLs ay OOLrsTe ( OOLsS2 aos ( 8 ftL ( Of ( OOL:02 ( 82 eS - OOLsVLL d88e 0006 .tokeulont tot ofdelisve som Bolsa ame oe tonasm ody at sonottttb otesd sno et stent cfs aro enotgoh eetsd sse1D odd nk sotade oft mOTR eens 1 30b to dnedxe oft bne nokfatgo rota .eg0b te) 98H 1g yifsisnsD ,.sonivorq oft ai bemesom yidaewoey a sonsiqooos ‘tognud of bis oes tiedd mf oniiceh & ak ome .Jeow oc Jase” edd mo etedaud gnome nolteevoetbh eysod erate sit ‘lo notsteoqmos et no bas 1s9b fo ef Bg6ne esssiyvoo ot gatatosl ebnvod stedw sesso to siash Some JI .doud onvel 8 yd tovoo wofdS to duo ma ny to ode1 odd JosT1s ot Aguone asdto | ve gia ae .39d od? of sitowd sai enwst viteluokiraq ,r90b anuoy gsds ais lqmos: gre trust ¢ enweat to {ftd oT +eg0b to cey ofgd ddiw belitl “eh anniiwsey gsatmisonos soncbtve oft bas besotinem foe oldstoninv eeel ots oste yous tadt sedsetbat jon ef etds tads ssnabiee at otodT ‘god ebostididorq #f egob to salt off B iuods ,ofistnO mistene ni cada 039 sBitmie® te9b ot asqo et getete sit ak soiling 1sito odd sXHifnU .zoonsotl yud ete Inet 000, wis" aatgoode ood oved yodd molgef sealed gee STRONY Ynem tot violiarsieon 3 eved 2@eL brs AeOl rot sevauo Lfta bigtt ttedz to. a botdolq need svac eoxsa SAT. - bssucvitanon pe gniixssy gadd cons hbat seb Of Juods syeigve yous ofimpond ak 9 i RCE bas [€ neswtod avr eogadneoteq sdoeoaniM od? edt tedid sidtgaog ef I - +0E Jyods opsTeve ee use of dogs is the factor responsible for this difference in the rate of occurrance of yearlings in the kill. Confirmation of this must await further studies. In commenting on errors in age determination in Minnesota at the Great Lakes Deer Meeting, Mr. V. Gunvalson mentioned that he thought some of his staff were over estimating age in the 23 age class. This might account for the relative scarcity of 24 year old deer in three of the four curves presented. Literature cited: (1) Passmore, R. Cz Interpretation of survival curves for populations of White-tailed Deer. Unpublished report. (2) Maguire, H. F. and C. W. Severinghaus, 1954: Wariness as an influence on age composition of White-tailed Deer killed by hunters. New York Fish and Game Journal, Vol. i tao °98=109. oilt at sonetettrb etds 10% ofdie to aotssmrtincd .iftb ode at 2 osenaiM mk notssaimioteb spa at etorte no see teds bonokinem noelevid .V .4M wntstesoM. ave eS oii nt sus gaisamijes tevo stow tage eb. £8 To ysioreoe svisalor odd tol gavoses ¢ ebotieestq coves Sot odd To could ate to? euvua Levivius to actdetorqiesnt SOeem eo 10oqo"! bere ifds qr et af bedteteage6Me o easnitsw 3icOL ,everuntisvee ow Fs) rid 9A rooG bolted~o3.i1l to nots tri: 10 efantmwol ome. bus det axoY ws FIGURE NO | CALCULATED AGE DISTRIBUTION FOR MORTALITY RATES VARYING FROM 20% wn wn <= ==!) oO lu oOo = 25 O = Ld = PERCENTAGE IN YEARS . oe oa EASTERN DEER RANGE : aa ear Se | iat: FIELD KILL CURVES ANNA LS +ORNENREREE eee ee SS ee SS -—s POSEN OORENERERSRGGE VUE PERCENTAGE. OF TOTAL “KPI AGE IN YEARS | se a FIGURE No 3 WESTERN DEER RANGE at FIELD KILL CURVES 70 1953 i a SE a a ee Sa a 1938 On OR Be Be SS —Ccrrh REET A 2 re | AT PERCENT “\ JAI % C = a be) - - x = 2 a ~ a ee ee : a ae a a oN eS 5 FIGURE NO 4 WESTERN DEER RANGE © io) ei — ae | (a a FIELD KILL CURVES ee Boel BAe PERCENTACE OF A a e £ =a - 100 90 80 o NEW YCRK WESTERN REGICN &o& NEW YORK CATSKILLS & NEw YORK ADIRCNDAKS & EASTERN ONTARIO 9 EASTERN ONTARIO FREED Kikic. CURVES osaSeneeEe MCKELECE ANAT A B C 70 0 60 50 40 30 20 A AL . a Hh ‘ Lot CHIE | Ma Gekko 7S ON NE A Sr rn nC Tf GRE eet ers oh A 3 ld Oo Me NT A AN ae oO to & BENT ACA a \ N AGE IN YEARS } | v t FF ee ges mate eg et a aoe a acocoecoe BEWCSSTITT : et = Sy =! x 4 jo) ~ ro) Hii Seat et hI SEREREEHE BCAA — Ui ~- 56 = DEER INVENTORY DISTRICT OF SAULT STE. MARIE AS be by M. We IL. Smith Meee GOSer POPULSECION L95h saconccnesccnceneserosanee 20,500 Estimated loss by predation and starvation ceecesesecceces 500 te Pee Oe cde 1955 sce ekeccncccvecececceesees§ 1,98h MG EMIMUCH TNCTEMENE cecccsesneccvccctucscccccccveccssesees 9,400 CE Gm MOMS LON 1955 sesscnscrccccsvccccccesees 219416 Data on which above estimates are 'ased: Estimated loss by hunting Non-resident hunters @eoeoeoeaeces eov0vec 612 deer This figure is based on a known total of 900 deer exported at Sault Ste. Marie in 1955. From deer checking station figures 32.1% or 288 deer were exported by non-residents from other districts, leaving the above total of 612 deer. Resident deer hunterS secescsscasescceees 1,122 deer This figure is based on a known total of approximately 4,000 resident deer licences sold in the district. Percentage success ratio of 28.06% was compiled from deer checking stations, deer weighing program, and 77 voluntary returns from the local Rod and Gun Club members. Farmer deer hunters cecceccceccaceccece 250 deer This figure is estimated from the estimated number of 500 farmers’ deer licences sold, based on a known sale of 195 by three issuers of the possible 28 issuers in rural areas, and with an estimated success ratio of 50%. Total hunter Kil eeoeoeooew ooea#se@eeoengnees @¢ 1,984 deer Estimated Increment; Herd size cTTocy Lee eee eT ee ee 20,000 BuckeDoe ratio: 1.321 or 11,500: &,500 Doe=Fawn ratios 121.08 or 40903: 4,410 Summary Three comparatively open winters have caused a steady increase in the size of the herd. While it is realized that as yRoTKavut aged AIAAM .aTe TIVAS qO. TOIATeTA ager y)* ; ia NG dzimne .2 LW MM O0¢ , OS essere eseossesessenesssese Atel Prt ean GO? cocescdécocecss MOLGEVIBTS DEE araeertalies | XY Lt ale. t ‘wasceeesbeteseetesuees Gees #2ef a iitsouc vd Be a) Ws, 2. scebacendes odducsucs Cuan taemeronk Bi eis. Vs eee eeoseeoereoeeoteeeecseesees e2 ef aottsaLuqog as9b shegsé e768 sevsmitge evods not San vd se0b Sid eeccucccccoevecese GtE0RUA Jnebleet=non hotnogxe teeb 008 to L[eio3 awond B no beasd ef eunit af eos roiisase aniiosds teseb mort ®ePL ak eitaM , tofgo mort etashieetenon yd beg oqxe a5 9" aseb .1e68h Sid to fatoo eveds eng oahveda ‘T6eSD Fi t ees eseeeeeereeeueuee eresaud rraeb jnebieea S Ssoinseib edd at bloe sesnestl r6eb sane f iiatoeris Ieen MOI. beLiaqmoo ESwW ‘Pao 3S to" fsc0l eft mort enrusor yessautov SV base .mB1NO7g 5 -etsdmen duLd . eer O02 a ‘eeeeeeececeeaevaester eretnun * gob sanr1e1 to edn betam 3s sdt moti bets niges ¢ si sma lt etr yd @Cf to sipse mwond 6 ao bessd , Dios eeonestl teob ‘djiw bas .eserw Isaist ot steveel RS sidteszoqg eit to 18 oRO2 to ofsar sesoous 3 to fseso3 wonxr & NO beesd et ormatt oe ae be ’ rey te ¢ : *¢ - 1 = mde -Yeeb AKO, 1 veeccccsecsveesseeees Suan SROnmN aan *gnement: 0. OS cteoceeSéeoveenseecoveaeenesd asre byeH o0@.8 :O02,f1 to I3€.L toksex soWestous Of4,3 °°: 0003 ro 8O.[sf :oidey avetesod ‘ybsese : B beauso ovsc etetniw aeqo yfloviga rsdn jad" besiieses ef 2i oli «bt eds. to + haa a 57 we population estimates based on kill records are subject to a large margin of error, the figure of 10% kill was used to arrive at a population figure of approximately 20,000. Other factors influencing this estimate are deer sightings, deer yard surveys, and general impressions gained during the past decade. The arbitrary figure of 10% kill was arrived at based on deer records from "Michigan Deer” 1949, giving a kill of 40,000 in the Upper Peninsula from an estimated herd of 400,000, While hunter density is much greater in Michigan, our more efficient system of an “any deer" season, with dogs, should serve to offset this lesser hunter density. agi B Ot toetdue ata’ Pre taney espe) sad 6 4p eviawe of beey sew LUD POL te Gauakh @ evotos? sodt0 .000,08 “levantxomgge to bart: BYoviwe sie tegb - sracuhchuish % “poob ots edamkies | ptas- ~obsoeb deaq efd gaiaab penias ano teae heend jg bovieets esw ILid OL To -ormgtt recat é be tit es anivéa ~CsdOL “aaa asa tno kat 0 - bted pedamks 2° 08 mont siventned rae A rom two ,fiseidokM of gecesia doom ef Yotene £ PN"LSE Bisonte: anob fitiw .fognes “xreeb ere? ie Io. he pt % we tteaeh tedmurt tedael 8. Ae { ‘ 58 = SAULT STE, MARIE DISTRICT NT WER WERK om ee SS we , SS SES SN Y, nN ‘ SE SEN ? i\ Sault Ste. Maxie Bea ed N\A “a bs —— ee rae” a Aa) : yore : § = Y AY ere North Channel Plan Showing = Comparative Abundance of Deer, 1955 WARE - 2 to 10 deer per square mile. Miles 20 10 20 4.0 | }- up to 2 deer per square a ee mile. TOLATELG STAAM. RT TYAS f <4 VN le ay aa ae are eer mgr ener ae Baa i, re j a = q a2 ‘ee Ye wd ie, » - 59 - ELK INVENTORY DISTRICT OF SAULT STE. MARIE He) Estimated population COC CCHCOL EL CED HOC O ESHER TC RO SESE OHBSESCEROC OS® 18 Sight records outside of previously known range eceveescoevee L (One bull elk seen in Township 2F, October, 1955, by James Haugh, Department of Highways, Blind River =~ see attached map) No known kill by hunters or predators. ~ Cl « YAOTMAVNT WI GIAAN .ATC TIVAS TW TOLATEL eeet ern 7. J = GE CoeePe ree Pere HERE TEKH Kee a tener tseeae nolielogog be . t eegecectoegeee Sanet mwonm ylevolvetg to ebLlasvo ebtoos <@guel eomel yd ,t2C1 ,todotoO , 1S gidauwoTt af aeee Afe fi (qem berlossts coe # tovin hails aso ew bas ,toitgeth edz sits: .ot@ ifuae éd7 af etedaud teeb Sneblast-nom to 10€,f yletemixouggs esw ek i a " a edt esw. metgotq bebasqxe end at agede ont "ori teeb eds. to aotsstwh elt 1t0T — eeteerM miesioo. yismitq tieiT .tisve feveso edd to etedmem oF fuof. .eten ed? davotds tdgvord t98eab iis datew ® ovew etal -bna bexvods stew exesaud Iyleessoveny bas seecoue-:tednud ed? .ebiso motsete gntdosio Laver ms anoivnog esbulod! dotdw. .Jofiterb edd To stag Ls13199 | R681 esw ered tnseeteel bus antgs: sifJ..26w MatRO79 bebnaqxs ofd at ~eotTl0 Jnomosenem oTrLbiiw edd ad ea bLolt noisso:tramacd e'jgottgetd set . bexoeds erew eqmeo-ta bas blett edd af at botsagnoo « etedsol-enstove Blo .barintew teeb theid bas etdatow toeb pre aw 62: = TABLE I - Weights of Deer, Soo District, Season of 1955 Males Females Age Average No. of Average No. of ee. Wt. (lbs) Animals Range Wt. (lbs) Animals Range ? 77 5 60-90 76 12 60-98 le 126 9 75-175 114 6 100-150 26 257 10 115-234 120 i2 100-175 33 162 5 115-192 114 3 109-118 he 197 6 175-211 - ~ ~ 5B 209 8 165-275 - oa e, Age Class Distribution Total Deer Checked: 259 Percentage of Deer Checked: PC EICKS 5.vssesse0, LOS Aaa Seeks: 4404. Peeks BLVOOe BEE, OOS ‘seeveccwees OL Waele Deed OAs ose vob 28 55% Buck Fawns @eocoodoooeoeseododcee 30 TOtAL Fawns eoooovoooecdeogedd 28.56% Doe Fawns esoseogooeeeseese Lh Undetermined ooooo o@e aeaao9¢ beZ I Unaged and Unsexed ...e 19 Percentages of Adult Deer in Each Age Class Bucks Does Sexes Combined Age No. of Percent No. of Percent No. of Percent Deer _of Total Deer of Total Deer _of Total 13 38 3519 35 57037 73 43.19 ae 28 25.92 20 3420/5 Lg 28.40 33 20 18.52 3 491 23 13061 4 LL 10.01 it 1.69 if 710 5 rt 10.01 fs 3425 13 iat Totals 108 61 169 Unaged LJ, 8 19 Grand Total 119 69 188 Average age of Average age of Average age of Adult Bucks 2.07 Adult Does 2.10 All Adults 2.51 Brief description of weather during the seasons: Heavy, district- wide snowfall November 3. Brief thaw, followed by more snow November 15, giving almost continuous snow cover throughout most of the season. ennen elas BO mOa O@ f-00.! 2F(-00L BL f=COL 4 : _ ' eacercion DSILGiNo. 2 ERR RU o te savor ip-3oT. 3 id VL.eEd Os. BS 4 Oe ct OLs ‘ ore }. sa _ 2.2% go lame’ - ‘Io OF efasiiticA. (edt). ii oe te0e7 to epecn: Senpenreeen.eaosae seeegcenmeewv oe 7 ‘even eseies BAL iO SRB SOBSIOVA.. 2.8. etfwFA IIA: -sJoivteth .yvseH Jecm .duodsuoid? 2.8 © 4 8 #..% k snosses sft woue ‘9'tomt xd. ‘howollol Ww. “Tesvoo wore eveuaisnos ean10vA e . 9-00 ALT. eV Lot AESHeLT Sel-2LL [iseal L =- eVSetoL otsd enmovd dLuBA esol -tIeDA wet: Laszot ben tanxetebnv orerereeaen J id setae covnse Bf Co cewe ro eeee eeveseesere Te s 784 oe as: a 2 Sa. 2enBl) esA dope aeod 2 ES I gas01si to -on intoT to se0G VE.Ve €. aV SC S [Qed 26.1 eS.€ ‘to ons SgRIevA to ¢ OLS eof oLbh. ; Lome uilo. akaeb | ‘tots ee ‘is Ballot Survey of Residents A further step in the expanded program was a mailed ballot survey conducted among 989 resident deer hunters in the Sault Ste. Marie District by the private marketing research firm of Elliott-Haynes Ltd., Toronto. The list of 989 names of resident deer hunters was gathered from the licence issuers’ lists by Department personnel, who selected every fourth name, to give a 25% sample, as recommended by Elliott-Haynes Ltd. This list of names was given to Elliott-Haynes Ltd., together with a supply of carborundum stone for gift premiums to be used in the mailed ballot survey, as per their recommendation. Details of the results of this survey are contained in a separate report prepared by Elliott-Haynes Ltd. The initial results of the mailed ballot survey revealed a success ratio of 32.8%. This figure was revised following a telephone survey of 69 non-respondents, to a success ratio of 30.6%. Buck=-doe ratio was 1.621. Doe-fawn ratio was 12.26. Other data secured from (a) Rod and Gun Club members who provided voluntary returns, (b) field survey party and (c) checking stations follows: Sex ratio = Bucks-does = 1.331 (Sample 255) Reproductive informations; Doe-fawn ratio - 1:1.08 (Sample 135) Does milking-not milking ratio - 1:1.8 (Sample 56) Ratio of guided to non-guided hunters (non-resident) - 1.8831 (Sample 285) Ratio of hunter success of guided to non-guided hunters (non- resident) - 2.6:1 (Sample 132) Days per hunter per deer (non-resident - Guided: - 11.3 days None-guided: - 12.4 days Percent success of non-resident hunters - 43.5% Resident hunters: Topeak Number checked ceusnescscvcesececacwesesene JER Number of voluntary returns (Rod & Gun Club) .... 77 TWO GECY CAMP TEPOFtS cececsancsvevsescccccesesse Lf Combined totals eosce@eoogoece@soeooeeeoeogee@#~cdcne@~edcecgseeeeo0dc 8 ee 426 Total kill eoecoogcoeeocoeocooeoenoeeoeoesvseeeeoeseeooeoeogoeeeoage eg 119 Percent success of resident hunters ceocccoeccsccce 28el% St. Joseph Island St. Joseph Island, with an area of 136.1 square miles, is the only portion of the Sault Ste. Marie District with a season less than 25 days in length. For the past several years the ten-day season has extended from November 15th to 25th. Prior to that it was fifteen days in length, extending from November 10th to 25th. y j y i i wee hak a. af « f= B 6s ts im } boliem & esw me1g907q- renal ene: nk jove neds prt at eves t90b dobre 280. aroms yovine © att dovesast siitedtan edsvitq) ert vd sottte kd sivah% 1098 9, _ woonet0T bad aomyst=sootL gw ataccin ve a tnobrest to: 2omsn e80 to ‘galt edt 3 ,Lennoatag IM atts oF yd edeatl ‘exveosel eonsotl edd mort tek BB , Tyme PES s ovky oF, peitsn dowwol yreve: sea ebid eomysh-ddot cits vd » eaw yor : id ,oJ8 tlust ody ab ere dana tenb_23enae cael id Ng ip. 2020g%tg oft: St iitso “gana % ‘gn viwoliol of iT ot mee = 4 ons: Joubnos-os body botem sa id 4 yevie gi * Y aie , + ~. AY) TUOMR ; , w8O-980L90 oft oF qu Bam For ons , Jaen “eee ’ told .£: ,ejngiidgid ont to ey: “Bio y « Btiwoda eelidas bas @jiueou odd To. ake : off ,bo#es aokteoup doas of 22S WER | > pwede oels Bt soliad exiannottneae: -' “.duoge off 1S a4 ) 2 SHLEO'E' Ge Ripe ejollad.:ovordw stow pesemiio: | rly nead . i) on bs doa2d eft’ ts ‘wiel i “xtbao qqA al nwor a" — ri toget ek 13 ae a PURPOSES ... -» This mail ballot survey was mainly designed to ascertain the proportion of Sault Ste. Marie district resident hunters who were successful in bringing home a deer. At the same time it was possible to determine other important data: the approximate number of days spent deer hunt- ing during the 1955 season; the township or general area hunted; the approximate number of deer and moose, if any, seen during their hunt- ing days; whether or not dogs were used and their Opinion on the use of dogs for deer hunting. in addition, the telephone survey among sSauit Ste. Marie hunters who did not return the ballot was designed to ascertain their approximate proportion of success in getting a deer. These percentages can then be projected to the total sample. Sule Gene aay ld ; eo - er aetna reipneanenetaseliit smmmesingaiaveratn cone onan sienna cab fee ne tm rete green ape pcan reat ate cules ae A . a . , x ¢ ‘ “ g~- PS: ‘Bee GhW. ~¥OoVeEe TOo wt ‘ Ps ry : i ~\ rao |. vitae Yo soitdoqots. - 4 F ‘ : , ~ hus sae reend sHereet _— « aw we Sl Ee 4 ws — ws See oe NB OSs > 0% UF: om” Ae ae % M * ® 5 < ‘ ‘od Diwcse L e F- haa J sk. Pe ~wh) J3- SOE . ' i > by ¢ rire aro rah oa "33 he ee Pehl awhad SA WAL a ad we peak: Bm eri oaks trees thee hi FR moesin amd KOE bina kd 2 SiN eA eee ED BD IUSLE TALS E Oy SRS HB of J ‘ ps = le eo -~ “ 3 * mpmecjswy :-2po et '- -} i = ee sf Leet 8 | e LVGSWS (CGE Bey s bo “ib” 2 - =" ™ i P a - » 5 e £ 4 a Ji ~~ «i Py ae | ee sLLS eid Sik 8: ; 4 : as aw ae “ ¢ .4 we rie ” fad cfr he ae bad as 4 tin we « CF aa (wa oom 4 - . a es ' -s— ~y? “ur ~ o * - Ae aw 4 \ 4 igh ad Bus id Ri roijedy m - z —* “3% h MY “ee - 7 BiiTay J Iw GHOO £0 Very Da mA ~ . Pa e | mal ee “a { (VV ac. oo LVL Sih fe “ J F : : : . as : P ie tan rer 4 : A wil £ { Tcaisl ‘ ’ i fh ; fe “4 ; , ; e mae 4 4! c ss METHOD . . « « it was calculated that approximately 4,000 resident deer licenses would be issued in the Sault ste. Maric District. Prospective respondents were obtained yy selecting every fourth name from the lists provided by the license issuers in Sauit Ste. Maric and surrounding district. 969 names were procured by this sampling © method and the initial mailing was done during the weck of December 12th, 1955. Ia order to get as high a return as possible, and at the same time to compensate for the time required in filling out the bailot, a carborundum stone was enclosed as a gift premium. f&. 24-hour post-card follow-up was made, reminding respondents to send in their ballots. 411 those who had not returned their questionnaire by January lst, 1956, were sent duplicate ballots (in case the first one had been mislaid) along with a covering letter (see back of report). This technique resulted in an exceptionally high return of 72.2% as of the close- out date (January 30th, 1956). This sample infor- mation is listed in detail on the following page. The special telephone survey was conducted by trained Sault “Hilvuow @a 7a: aSue wehbe fost. +E ee LIBWRHST RS BH br elivel dolwaet % ik goteksqaos Vines Janot jem aOe gh { suxs soto ¥igo wit ~ vgueiae vhs Hig iaG (seqodT subpeione do idw e Peni poaoyas: ods to esa ree © . morta b és {iziw: i, soFaeedG! ota (ede ‘tyon Seat ; we yoed? ora gitaege tou bivow ne *s f 4 + \ ; ‘ (El jdat of Gi) 5 a as ’ > ef » * x , +f my a . > La p i ey ’ % eis F , uy otis Weupi ‘ | Raa ey sa nena rh CUNO ST se Leon! fd ir «5 When asked the approximate number of deer and moose seen during their 1955 hunting days, more than three out of four hunters (76.5%) reported seeing one or more deer, while only one out of five (20.4%) saw one or more moose. The average number of deer seen per hunter was approximately three (3.4) while the figure stood at .5 for moose. When broken down by the number of days spent hunting, 65.5% of those who hunted for three days or less saw at least one deer and 16.6% saw at least one moose, The ratio increased steadily the longer the time spent hunting, with the result that 87.4% of those who spent more than ten days hunting saw at least one deer and 29.1% saw at least one moose. (See Tables III (a) (b) (c) The main question on the survey pertained to the degree of success experienced in obtaining a deer. Almost one third of the hunters (32.8%) indicated that they were successful in bringing home a deer. When asked what it was, the ratio was indicated as follows: Buck - 55.4%; Doe - 34.4%; Fawn - 8.9%; Moose - 1.3% (See Table IV) Comparing the relationship of deer kills by days spent hunting, the results are very interesting. Those respondents who hunted for three days or less had almost the same success ratio as total re- spondents (29.7% as against 32.8%), which would seem to indicate that these hunters broke camp as soon as they obtained a deer. Only 1¥.5% of the hunters who stayed for four or five days were successiul, while 41.5% of those who hunted for the cxtra day or two (six or seven davs) managed to bring home a deer. This "success" percentage stays relatively high for respondents hunt- ing eight to i0 days (39.9%) and over ten days (37.9%). (See Table IV(b) ) The area in which the respondents hunted had a bearing on the pro- portion who were successful in getting a deer. in the Sault Ste. Marie District it would appear that Areas #5 and #4 had the best record (62.5% and 35.5%, respectively), although the base of & for Area #5 is an insufficient sample from which to draw conclusions. The same holds true for Area #1, where the base is only 23 and the Success ratio shows as only 21.7%. Areas #2, #G and #3 are almost identical, with 30.8%, 30.3% and 29.1% respectively. (See Table IV(c)) sh ie ’ . \ ‘ AS: i , ht 7 fe j Dutt ; ; 4 en, 7 ; J re at iyo c i rp q') 1 a ; i A ¢ ivd = | Wks d AS { ' f 2 “ a7 ai «) ; 5 ad 4 ; r hy } rescya Gj « a. stot ‘ ey ' 2 Pe « i. , j J ay i? ‘ Pad q { “ae + we f “a - ry, g : % ERD: ; OO Ss 1600 ; i i eae con Soho ee Cas i | C , i lw e Acre ‘ ioe - a i 12OOM 2 tO ‘1 TO. prs Posy e + = s 7 yf . Ls a te | ¥ ; yen . a+.¢ tt { ; Wi abe Vis Sl SMGLRO* tc igs. (SSW, Y AOS BY a 3 j OE i paw . hae Pn : Sst = +, Pa " : . ae oft botnud x £8.88 gt EY AT ; ; + Dis “used os d . STR E. nois ofom taeqe olw apie to. oom tag eS bae 195b (dx a) a) SS ie = ; y ; gory aT igs , a E i ; a ee au f ¥ gLiaan otis! re itaoxo? bet NGSe@ ; wed ; aa 38 AN % ow miso 940Td axes ; F si al as | f ee W aso ry f non “Y tdi 9 eT pasa ’ Ji : - a * : : (iG c i sf NY J [ont sil 9 : ) «€ } Ie ; ; . ‘ i= ' bait Bestrud nogeor eft dak . - - -_ j , i id Ae iBavos 2ua 9 ; oth Jandy saeqdes binow TL G id eg29" rs oe) bas ‘ nao ii elgqnse dy ek tennis leg + 9todw (i gsexA tol suad : bs (A * Xiao an ewor Via 20% at. 2c. 0b ce OCF r 7 ‘ >J 244 iJ ANALYoLe €con't):./ si... . faen the hunters were asked to indicate whether or not they hunted ith dogs, 21.7% replied that dogs were used. Almost four out of five (78.0%) indicated that they did not use dogs, while a negligible proportion (.3%) did not specify. The majority of hunters (52.1%) are opposed to the use of dogs for deer hunting. The remainder either favour the use of dogs (37.4%) or do not take Sides on the issue (3.5%). It is interesting to note that 11.5% of those respondents who used dogs are agoposed to their use, while 23.5% of the hunters who did not use dogs still favour their use. (See Tables V & V (a)) Comparing the relationship of deer kills by whether or not respondents hunted with dogs, it is evident that the use of dogs increases the success ratio. Of the respondents who hunted with dogs, 41.9% were successful compared with 30.3% for those who did not use dogs. (See Table V(b)) Considering the special Appendix Table which shows the results of the telephone calls conducted in conjunction with the mail balilot survey, it would appear that the minority (255) whose mail ballot was not received, did not get deer in quite the same proportion as those who returned the baliot. 69 Sault Ste. Marie non-respondents were reached by telephone, and 24.6% of this group indicated that they were successful in bringing back a deer. This figure compares with 32.8% obtained on the mail ballot returns (see Table IV). In order to estimate the probable success ratio of the entire group studied, it is possible to apply the percentage of 24.6 to the 255 non- respondents. Therefore, if the entire group of 255 non-respondents had either been contacted by telephone or had returned their mail ballot, it would probably have shown that G63 of them had brought home a deer. Grouping this figure with the 224 mail baliot respon- dents who were successful in getting a deer, and appiying this projected figure to the actual sample base of 937, it is shown that 30.6% of all hunters in the Sault Ste. Marie District met with success on their deer hunting trip. (See Appendix Tables I & ITI) Applying the same technique to the question concerning whether or not dogs were used whiie hunting deer, it appears that the non- respondent group does not make use of dogs to the same extent as those who returned the ballot. Out of the 69 non-respondents con- _tacted by phone, only 13.0% (9) indicated that they used dogs. This figure compares with 21.7% obtained on the mail bailot returns (see Table V). Applying the percentage of 13.0 to the 255 non- respondents, it would probably have shown that 33 of these hunters had used dogs. Grouping this figure with the 146 mail ballot respon- dents who said that they had hunted with dogs, and applying this projected figure to the actual sample base of 937, it isshown that 19.3% of the Sault Ste. Marie District resident deer hunters had used dogs while hunting deer during the 1955 season. (See Appendix Table III) . , MM é ee F | } eto ras . s ; eT | ‘ ae) } a : . H L it obo el be | Sakae » P : , i ee Pe ts ; ma ji - Aw, -. SRO cra ’ iw bd be B - ren’ yeh Senco ton hen Gee oe : . af. SLs +¥Si9G02 JON: Os st SOs P19qQo 7 = 4 a) j vs ra 6 ‘et ee ~ ' "" BLT pou, 0 » ‘tos 1y OF; beeogqe’ ohm he ’ ' ; : ior pkey n% > : \ ‘he . Shaw (ova sS FEA 5 Dd “5 > 3a. 4 etd es I. othe. SP; ‘oe . 7 ’ ‘ ’ eee & Sir Aer 2 “> ‘ vt E - J 3 rw au jay View. S FF: orn & atuobne ‘ . Tri E ; =a rim oo stews 4 : hs oe ot Ml: Wk: OW 2°iv SOUR ‘. ’ , ona BOG € b io ati ' ; 5 # Jha » wey . y wea 7 sah . a5 +h r “ o * al - J - 7 - a 4 ‘ . 4 va . ‘s ’ ee. | J { ‘ ; *, t f43% . . - ‘ ~ 4 : - 1 bw. 4 5 ‘ 4 ' , Vu ® . > i ; | ; L wt q ~ 7 } - ‘ u w ’ . . Uh, : : : . ee rer fe vos 3 , Ay a oe ‘ ; . aii itv ‘ a ' ¢ , . . A .! a t . u ; rWistk \s ‘ Z j . [Ty = ‘ » rt ry ~ LWwiee vooue < A Sil d BuUToOL ung " ox Re - iy ; +s r A ‘ 2 “y } a : } oil ). Sav trims df J ' sntzawd us0b 2k 7" i. Ad WD 'L vessel + : bets £3 tt . — ) 2,eu. Bae: 2o i aw . 7 4 x a ‘Ue a ; ee ‘ 4 ‘4 J be , - Niro 2) oe | 2 , | . , «ee (un: born it (Qe y : ofr, See ee i e oe ty ig Mw cche RA ose 1d F , A , ‘ a + 7 ra y y 70 - ' * . - 4 2 ° - de ok i ~ x - ‘ee hs A ba oT a a +e dn oe aw Cee nae a 2 fl tL eg oe fh io * i cory® Tt = 7 io O@ Les ri 4 Rn = ® og " ; j f : (: “Approximately how many days did you spend hunt-— ing during the 1955 season?" BASE G82 ~ 100% Three days or less ‘14542 21.2 Four to five days 162 - 23.7 Six to seven days 123 - 18.1 7 Se 148 S21 57 More than ten days 103 - 15.2 Unspecified 1 - a AVERAGE NUMBER OF DAYS 6.9 days 3 SPENT HUNTING \\ — s- TABLE I (a) DETAILED BREAKDOWN OF DAYS SPENT HUNTING EASE GE2 - 100% Days 1 Si - 4.5 2 46 - 7.0 3 66. — 9,7 a 56 - &,5 5 104 - 15.2 6 42 - 10.5 @ 51 -- 7.5 3 46 - 6.7 2 17 =+ 2.5 10 65 - 12.5 ig 5S - of” 12 29 - 4.3 13 Z2- 3 14 23 - 3.4 15 Zi- 3.1 Over 15 days 23 - 3.4 Unspecified 1 - al TABLE II QUESTION: "In what township or general area did you hunt?" BASE 682 - 100% Area ey 23 - 3.4 2 201 ~- 29.5 3 266 - 39.3 4 93 - 13.6 3 8- 1.2 S) 109 - 16.0 Outside of District 32 - 4.7 Unspecified 6 - 1.2 NOTE: Percentages total to more than 100% due to respon- dents having hunted in more than one of the designated areas. See Map at back of report. "S Jou voy Lib nox Léxoney ps3) qidaawod' tee egos ~ $58 * * @ ~~ G % & Re é @ ae! O.0L - gOr +2 - §t saixtaimd Io vbtesuO 2. FS 8 bolirougeut -“nGualga o3 sub £605 wad eget GS eee 2ogieob vit to ono cedd rom ab Bosnod gee .?i0qe% to doad 32 gall wets . Pe a a tie " ~ 7 , a i uf e 7 : r , a, 7 i f _ } 7 J @ Sear he | Ba 1 blame cs of a ("Approximately how many live deer did you see during - your hunting days?" BASE: BASE: TOTAL HUNTERS . COMPLETED SEEING ONE LUTERViZWS OR MORE DEER 682 - 100% 522 - 100% DEER SEEN 121i ae 23.2 98 14.4 18.8 63 14.2 15.9 64 9.4 12.2 44 6.4 8. 33 4.8 6.3 17 By5 ee! 14 2.0 257 8 se 1.5 ; 17 2.5 3.3 / More than te = 23 3.4 4,4 “Didn't see any deer 160 23,5 ‘ re AVERAGE NUMBER OF . 2 DEER SEEW 3.4 4.5 2 gatell 5 Meh reat hates ali pettub oda woy bith sesb ovit-yaom =“ eee ee or ; 4/1 LONE BAS ; iiOAE dts, THs AATOT eNO. DSTO -. GELTaMGS HOGG BHOM NO - PIGS Hui > 385 ROO ieee | &,. £8 ee fe | i _ a OF GG . Gs vad : $3 $< Su ».¢ 5 +. 5 2.8 , Ged aye és . wet acs : Vi 3.28 ODL 6.2 be | De pay ror ; itu TABLE III (b) QUESTION: "How many live moose, your hunting days?" BASE: TOTAL COMPLETED INTERVIEWS 6&2 - 100% NUMBER OF MOOSE SEEN 1 GE 9.7 a 21 aka 3 21 3.1 4 13 1.9 5 & 1.2 6 2 3 . 5 Be & 3 5 Didn't sce any moose 543 19.6 Average Number of Moose Seen if any, did you see during BASE: HUNTERS SEEING ONE OR MORE MOOSE 139 - 100% a 5 ae Tuy é. Tea + * GERTTE: : pce ie Ms Sao i mon SHO HO edi ed | Ce tos 298 gov Lib eis Ti .9800m pare "Waves doa “DEAS "Oy “Ganhseuon ‘aes sa Roc! ~ S$8o | ee o.@) Ch@ oncom yas eca F%a es Lae é - . AST oe oy sea aan s KEE ’ to ten days : 4 » iad be ; = Z i. than ten days INSTANCES OF SIGHTING DEER OR MOOSE, ~ BY LENGTH OF TIME SPENT HUNTING SAW ONE OR MORE DEER © (oy) i Sj or: G = dN isy) ! ee) Oo j SAW ONE OR MORE MOOSE 139 - 20.4 oe Me hy ab Ta 2 EOGU fO Aaa OMI THOS OMITHUN TWIG SUIT FO NT 10 YO Ae RD YMQ WAS TeCon. 220M FEEG AHO Ss G.ce a Gh QUESTION: "Did you bring home a deer this season?" y BASE S82 - 100% Yes 224 - 32.8 No 458 - 67.2 "What was it?" BASE 224- 100% Buck 124 - 55.4 Doe 77 - 34.4 Fawn 20 - §&.9 Moose oa) as é ha ? Pe y : coe 7 2) a ; (ear | , i] he} rh hed ie ee : hea AY * hl) i) y 8) ; aa ete a ie f, re os A \ ny h » ME rf vn (ohare at Ey " "Orme noe f; Phi gia och : ‘i i, so (omod Jaguoud ‘ane sat 2 ie ‘"T7k sow tem ROOL BSS d.é@ = ase @.8 = 0s goes ale io . y a a fey) rier ta Thay ta v ( : i ; Lf at 7 > ‘ > at ae 7 ) aq ( ! “9 A ; ‘More than ten days ae E ; , Inspecified =F BROUGHT DiD NOT HOME — BRING HOME A DEER A DEER BASE-100% 145 43 - 29.7 102 - 70.3 162 32 - 19.8 50 - 60.24 123 51 - 41.5 72 - 58.5 1468 59 - 39.9 89 |--)60.1 103 39 - 13719 C4 - 62,1 1 - iL = 100.0 (See Table I) fx Tah te Pir VNIINU THEME avAG Ye \ TO. ard THOUORS oe * 4 “oe “a 3 & Oo’. - FE fers} * nr ' on ow aw Cet 2 so BASE - 100% 23 201 7 238 } 93 8 109 ae is Outside of. 32 Seay District Ur specified as aut ‘to area 8 (See Table II) HUNTED BROUGHT HOME —, A DEER 12.5 DiD NOT BRING HOME A DEER 87.5 TOW Cid SMO OUT RE RagG A — wha) ae yaa 4) lie ny a Oe Oat a ee j ' ; 9 GITHUA AIHA ¥a ‘Taovuosd aMOH ARUAG. t . . . yA fs & a a) AS > 23d whe: +3 iri ———— va TABLE V QUESTION: "Did you hunt with dogs this year+" BASE 682 - 100% Yes 146 - 21.7 No 932 - 72.0 Unspecificd a = oo TABLE V (a) CUESTION: "Are you in favour or opposed to the use of dogs deer hunting?" TOTAL HUNTERS HUNTERS NOT BASE USING DOGS USING DOGS BASE - 100% 682 148 532 In favour . 255 - 37.4 129 - 87.1 125 = 23.5 Opposed 403 - 59.1 17 =~ 11.5 885 - 72.3 Depends on the 3 - 4 3 - G locality Doesn't matter, 3 - 4 ~ 3 - ie immaterial Depends on the dog 1 - 2 ~ i - 2 Just until snow comes 1 - 2 i - at - No opinion unspecified 16 - 2.3 1 - a | 25 2a 8 in UNSPECIFIEL "Saa0,y eidd egob ihe tasd goy ayob tu cay Salt ot beaoqge . 10d BABTHU = ameTwon iG 800d ‘duraU | good ByIsE ——~ 853 eS 1 e,28 ~ ese ‘¢49)s epr evRY = ace. eler oe TABLE V (b) INSTANCES OF DEER KILLS, BY WHETHER OR NOT RESPONDENTS HUNTED WITH DOGS BROUGHT DID NOT HOME BRING HOME BASE - 100% A DEER A DEER Hunted with dogs 148 62 - 41.9 66 - 58.1 Did not hunt with dogs 532 161 - 30.3 371 - 69.7 Unspecified 2 1 - 50.0 1 - 50.0 TOK Gid Vit 4 4 ml a" \! Z oy CEr DID RETOUR) CooL eTEr TOLAPHONE. CALL ' 2 . ans 2 ‘ \. RR. "ieee Yow Ways oulur 1. : a - Ne a aT j e*> ‘@eaece ’ oa BARS i. | FABLES "Ola be ui Babe te tdry ‘ ‘ a! oe tus >) i - Dlr ODWNG | PPesosvec an ‘i Preprrca ~Jik ve [ + j f 9 i> ~ Sa Z gf ie > | t at & 2 Ca y un _ as ve, Sine @ APPENDIX TABLE I FELEPHONE CALLS AMONG SAULT STE. MARIE RESIDENTS WHO TOOK OUT A DEER LICENSE, BUT DID NOT RETURN THs MALL BALLOT TOTAL COMPLETED TELEPHONE CALLS G9 - 100% QUESTION 1: "Were you successful in bringing back a deer this seasonr" BASE cG - 100% Yes 1? = 24.6 No 52 = 75.4 QUESTION 2: "Did you use dogs while hunting deer this se~ BASE 69 - 100% Yes 9 - 13.0 No 60 - 87.0 An additional 11 telephone calls were completed but the replies were dropped from this sample because the actual ballots were received and tabulated in the interim of the list being prepared and the phoning completed. , - - s 1 . a i ia ia i La LZ) - a. — aay # ; Sot ae) Tee ee ae : ; ae 7 Mia OHV SYUMOIOER BLAAM ave TMUAe -OHOMA. TOdiad JIA SHT WAUTEH TOW GIG The wemOT, oor. e@c’- » . | QD SMORGIOT GrraaEoo ‘op alddy: «sob gaisaud elidw egob veu voy bia" = ROOL - ed 0.éf = 3 oT #2 0,88 = 08 : As LD ae ¥ 9S a ae ong ‘tud beotuelqmoo oxow eligfo S1Od {sutos edt ceusoed olqmee ard? gout be of? io mitetal odd ai betalndsy. bove -botelcmos yatnong edd bea wel i a «tee Ae wer oy, nr a * APPENDIX TABLE II BASE PROJECTED ESTIMATE OF DEER KILLS IN THE SAULT STE. MARIE DISTRICT Successful in bringing home a deer non-respondents. 69 of the non-respondents, The actual procedure is as follows: a Not successful Completed ballots as of the close-out date (Jan. 30/56) Successful in getting a deer Contacted by telephone Successful in getting a deer Ballots not accounted for as of the close-out date Estimate of their success in getting a deer (Obtained by applying percentage of 24.6 as derived from the telephone contact) 937 - 100% This figure was obtained by combining the mail ballot respon- dents who indicated that they were successful in getting a deer (224) with the estimated comparable figure (63) for the This latter figure was arrived at by applying the percentage of 24.6 derived from the telephone calls among to the total 255 non-respondents. 1% = 24.6% 235 24.6% or 63 ,YT YT: poahnencrupt diab Fe | re? Bt /_“ SAAS A ide OS oh Mont. tadz vehi Sade by tamiteo oft. Atte “ottal aizdT. 869 bovitsbh o oa Le ORs oj} ,2tnobsaegesr- { slot ea.al oxpbosowg Ems ba, og to Be atoliad: é (% ,6\06 8b) o1 ye kb ies le s ‘ or »s ii $ a a4 ae @ ~~ — ¥ rt be tawe JOOS - 9¥a2b 1110 oO ag INE ators, 20. 3d om. yey Saka 30 is APPENDIX TABLE III PROJECTED ESTIMATE OF THE USz# OF DOGS DURING THE 1955 HUNTING SEASON BASE 937 - 100% x Hunted with dogs 181 - 19.3 Did not hunt with dogs 756 - 80.7 This figure was obtainca by combining the mail ballot respondents who indicated that they hunted with dogs (148) with the cstimated comparable figure (33) for the non-respondents. This latter figure was arrived at by applying the percentage of 150, derived from the telephone calls among G9 of the non-respondents, to the total 255 non-respondents. The actuai procedure is as follows: Completed ballots as of the close-out 682 date (Jan. 30/56) Hunted with dogs 148 - 21.7% Contacted by telephone 69 Hunted with dogs 9 - 13.0% Ballots not accounted for as of the close-out date 255 Projected estimate of the use of dogs (Obtained by applying percentage of 13,0%, 13.0% or as derived from telephone contacts) ike ie) ) ra a PAN! » VOL BFS 7 : t) \ \ Po a i ‘ i) ‘ HD Js ‘ et ‘ yo m dn La ‘ Me 49 f\ , i ; i . y, ea te jin a 2 * - ad ‘we ~ “ * oe r - “ r - eh MUAH Céel BHT oO re ee i th a PN ome we Mii Sasa f ‘ . _ hy r Pa 3 J Wiis W | ia ¥ « 7 - ’ J f1 3 iz oe 6 . a: ‘at « “ ere iy es rr Put? 2 we 4 . be e gl 5 ” ante ‘ , - - - esau eso ‘ - ~ ._~\ \UG >oyu off Fo Mt astee boa: o19¢ sckyviqas vd beak er al La > of * MINGLE +k Lovi ta dl T 36 CT AML TOS ee RE ea ete ye ¥ tee, wat “ ‘ ; { > = &} > ; idumcs ed box LOTS CS wos. ; “5 > coer IW Desay Vol fl = Te? i 10k betaveson’ tor | otal cont Jue -Gi ELLIOTT-HAYNES LIMITED Marketing Research 515 Broadview Avenue TORONTO G6 - Ontario Tuesday, January 2nd, 1956 MEMO TO SPORTSMEN: Just before Christmas we sent you a survey ballot requesting some hunting information for the 1955 season. We also enclosed a carborundum stone, in appreciation of the few minutes required to fill in your bailot. AS we have not yet received all the replies from your area, we are sending you another ballot in case yours was mislaid or lost during the holiday season, and we would very much appreciate your filling it in and returning it TODAY. If, by any chance, you didn't receive our first ballot and carborundum premium, please mention it on the ballot, adn we will send another one for your co-operation. Yours very sincerely, "We EH. ELlvett" W.E. Elliott President, iowseesA saitcdra ssaovi wotvbsoid GiLé ovtteinO - 3 OTKMOHOT Poe et ori: esis S22L: .. bHS varsuceab fxpopoet, # ua tat ee + yoviwe 2 woy tgo2 ow anata citi e1¢ked seb | scG{ ofd “wot ceitemuct:: yatiiod sage guise ou sit .oacia aubustod4n5 B beaGl Six “ta if. wwoy af [fst od bealupet gedyato wae. ty 2. ‘ 7 : f el we < asilgo. oft ils’ bevisesex For Fort over ow ‘a v2 us SOilsd todicre uoy gelbise ean oe yaaa BES ,ccerus yobiiod ods guisel ¢eol ae Digs ake ban ak tt. gefilsr MON ossioexqge doum Ye , YAGOT qwe ovioset t'bkb uoy- -seagdh wae yd Af neigcnom oaseiq mus imorg muhiu xvod Tso bar | ae , Ran eee nteQ toixgeld-oou 4 YK aL LSet a eOk) Maeaae tam